Projects

Turn a Board commitment into measured value in the core of a higher-education group serving about 360,000 students in Brazil. In June 2025 the Board approved a program with a goal of BRL 100 million in measurable impact (revenue and efficiency) by 2028, split into four value streams along the student lifecycle: Enrollment+, Collections+, Service+ and Teaching+.

Each stream has a business VP as sponsor and a technology leader as operational owner.

Goals for 2026:

1. deliver BRL 20 million of measured impact in the year; 

2. raise enrollment conversion with an AI sales agent; 

3. move debt renegotiation to self-service; 

4. resolve student requests with AI agents instead of human queues; 

5. cut the unit cost of academic production and grading; 

6. report every result with period, baseline, method and owner, without double counting.

Most AI programs report pilots and adoption. This one reports money and refuses to count what it cannot prove. Three choices make it different.

First, one case, one value stream, one P&L line: a predictive model never claims value, only the business unit that acts on it does, which removes double counting across four VPs.
Second, every number carries a class (observed result, partial estimate, scenario, theoretical ceiling or operational indicator) and is reported with its class. More than BRL 19 million of gains reported by the teams were left out of the 2026 count because they were not incremental or not attributable.
Third, AI agents run in production in the core of the business, not at the edge: they qualify and enroll candidates on WhatsApp, renegotiate debt, answer student requests and grade admission essays.

BRL 35.9 million of measured impact in 2026 up to 5 October, against a BRL 20 million target for the year (179%): Enrollment+ 29.6, Collections+ 2.3, Service+ 3.8, Teaching+ 0.2.
Enrollment: AI interaction to enrollment conversion from 11.0% to 12.5%; enrollments in the two main entry routes +15.1% with 8.6% fewer applicants.
Collections: BRL 2.26 million net P&L effect, January to August. Service, brands with AI agents: bot containment from 13.3% to 44.0%, first-contact resolution from 27.7% to 49.5%, satisfaction from 33.7% to 58.6%.
Teaching: essay grading cost from BRL 4.90 to BRL 0.11 per essay across 34,286 essays; 96,000 simultaneous users on the first day of classes with no incidents.
2026 figures are pre-close and subject to year-end reconciliation with Finance.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Transform the higher-education experience through a scalable generative AI learning copilot that combines personalization, academic rigor and operational efficiency. IARA was created to address critical challenges in student engagement, content overload and personalized learning, while reducing repetitive faculty work. For students, the goal was to increase autonomy through multimodal learning support, competency-based assessment, personalized leveling recommendations and academic wellbeing monitoring. For faculty, it was to automate assessment support while preserving human academic validation. At institutional level, IARA aimed to establish a secure, scalable AI capability that reduces technology costs, strengthens educational innovation and creates reusable GenAI expertise across the Ânima ecosystem.

IARA transforms generative AI from a generic assistant into an academic learning copilot built around pedagogical governance. It combines validated knowledge bases, Ânima’s competency framework and mandatory faculty oversight with multimodal GenAI capabilities. Students receive personalized support across text, video and audio in three languages, competency-based assessments, leveling recommendations and academic wellbeing monitoring. Faculty gain AI support for competency-aligned question generation and open-answer correction with personalized feedback and grade suggestions, while retaining final academic validation. Designed for scalable use across the ecosystem, IARA brings personalization, assessment, wellbeing and faculty support into a single AI-driven learning experience.

IARA delivered measurable financial, experience and quality outcomes while establishing generative AI as a scalable institutional capability. The project eliminated BRL 1.5 million in SaaS contracts related to assessment support and avoided BRL 1 million in implementation costs for assessment solutions supporting the Competency Test and Academic Happiness Index. Veteran students participating in the 2025/1 pilot recorded NPS 6 points higher than non-participants. IARA also eliminated spelling errors and missing justifications in AI-generated exam questions. The project reached breakeven in six months, with estimated 2025 ROI above 100%. Beyond these measurable results, IARA is now used at scale across the Ânima ecosystem and has generated invitations to showcase the case at partner events, particularly national AWS events.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aimed to turn isolated generative AI initiatives at Uniube, a non-profit university in Brazil with over 60,000 students and a university hospital, into a single, governed institutional capability.

Its goals were:

1. Reduce manual workload and processing time in academic, administrative, financial and HR processes, such as essay and open-question grading, student service triage, résumé screening and document handling.

2. Integrate the AI agents into the institution's core systems (virtual learning environment, academic management, student service and digital registry). 

3. Establish a common governance model, with safeguards against prompt injection, interaction auditing and regulatory compliance. 

4. Extend the approach to the university hospital. 

5. Measure results against baselines to support investment decisions.

What sets this project apart is that the agents were designed, built and operated by the university's own IT team, not bought as off-the-shelf products. This allowed each agent to be tailored to real institutional processes and integrated directly into core systems. Three aspects make it distinctive: 1. One governance model for the whole portfolio. Every agent follows the same safeguards: protection against prompt injection, auditing of interactions and regulatory compliance. This is what turned separate pilots into an institutional capability. 2. Breadth within a single institution. The same approach serves academic, student service, HR, financial and accessibility processes, and is being extended to a university hospital, a very different regulatory environment. 3. Build instead of buy. An in-house accessibility agent replaced third-party tools, with documented annual savings.

Cumulative results since each agent's launch. Some agents started before October 2025, and the expansion phase ran through October 2026. 

• Student service: 124,900 requests classified by AI, with 96% accuracy on the first attempt (baseline: 20,488 requests in the period before AI). 

• Essay grading: 79,280 essays graded, saving BRL 396,000. Open-ended questions: 30,656 graded; analysis time fell from about 40 to about 4 minutes, saving 1,660 working days. 

• HR: résumé submissions rose 68.9% (from 190 to 321) after the selection process was automated. 

• Accessibility: an in-house agent replaced paid third-party tools, saving BRL 49,177.52 per year. 

• Hospital: a first-level support agent is being rolled out.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The goal was to automate FAF calculations for the Hang Seng Family of Indexes using generative AI, reducing manual effort, accelerating financial data processing, and improving the analysis of complex corporate structures while maintaining high accuracy.

This use case is designed for internal use. The project’s most innovative and challenging aspect is enabling AI to apply financial expertise across documents with varied structures. It maps corporate structures and shareholding relationships to remove duplication and identify hidden shareholders.

The result is high-accuracy, high-impact data analysis that supports globally used benchmark indexes.

This use case aiming to enhance productivity in the index calculation process and expand data analytics capacity. This capability is integrated into the index calculations of the flagship indexes and more.

Impact Highlights:

• Enhanced Operational Efficiency: Lead time for FAF calculation has been reduced by two-thirds, allowing for more frequent client updates.

• Expanded Data Processing Capacity: The solution enables a 4X increase in data processing capacity, positioning the company to handle a more complex and dynamic capital market.

• Reduced Human Workload: Automation has significantly decreased manual effort, allowing the team to focus on product refinement.

• High Accuracy Maintenance Journey: Accuracy now stands at 90%+ with ongoing optimisation.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Guarantee the integrity of proof of delivery across a nationwide last-mile operation handling about 1.000,000 parcels a day. Drivers record each delivery in the company's mobile app with a storefront photo and a recipient signature, but blurry, random or covered photos and signatures made of dots or scribbles were undermining trust, generating customer complaints and support rework. 

Goals: (1) automatically classify, in real time, whether the photo shows a valid building facade and whether the signature is genuine; (2) give the driver instant feedback so the error is fixed before the delivery is closed; (3) run fully offline on low-end devices, in areas with no connectivity; (4) reduce delivery-proof complaints and fraud; and (5) cut the support cost of handling inconsistencies.

The AI runs entirely on the driver's phone, offline, at the moment of delivery. Instead of auditing proofs afterwards in the cloud, the app checks every facade photo and signature on the spot and asks the driver to redo it before the delivery can be closed. To make this work on the low-cost phones most drivers use, the team compressed and quantized the model from about 90 MB to under 3 MB while keeping accuracy above 95% in controlled tests. The training set combined real delivery photos, labeled together with the operations team, and script-generated samples simulating scribbles, poor lighting and odd angles. At national scale this has already caught and corrected 431,000 invalid signatures and 353,000 invalid facade photos, for an investment of roughly R$ 20,000. Edge AI turned a fraud-control problem into real-time coaching for drivers.

Results. 431,000 invalid signatures (7.8% of records) and 353,000 invalid facade photos (23.4%) caught and corrected at the moment of delivery. Delivery-proof complaints down 15%; estimated savings of 350k in rework and complaint handling over 7 months; investment of about R$ 20,000. The solution runs at full national scale.

Next steps. Reuse the compression and monitoring approach for other offline AI use cases, such as real-time quality control at other logistics stages.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Build RADAR as Union Agener's enterprise AI backbone for pharmaceutical manufacturing by turning daily operational discussions into accessible priorities and information aligned with the strategic plan. The deployed phase analyzes meeting transcripts, identifies critical and priority activities, retrieves information from earlier meetings and automatically distributes summaries across site TVs. It also connects 6,000 sensors for real-time performance against targets and lets department owners manage local TV content in the same system. Development ran from December 2025 to April 2026. The next planned layer comprises specialized Quality, Production and Engineering AI agents.

RADAR closes the gap between information shared in daily departmental meetings and the employees who need it. AI interprets transcripts, classifies the content, identifies critical and priority activities and retrieves earlier meeting information before automatically distributing summaries across site TVs. In the same system, department owners add information specific to their teams. For example, Quality can include release-related pending items listed in SAP to make the area's daily priorities clear. Combining common site information, historical context, departmental content and live performance against targets makes RADAR a foundation for a shared operating language and future AI capabilities. Specialized agents remain planned extensions.

Organizational climate surveys comparing 2025 and 2026 showed increases of 72 percentage points in site-wide communication, 43 percentage points in perceived employee engagement and 35 percentage points in trust in site leadership, as confirmed by the executive sponsor. RADAR supports access to operational information for an estimated 200 employees through the Daily Update and departmental TV displays. These survey outcomes accompany the rollout and broader site transformation; RADAR is not presented as their sole cause. The site forecasts a 45% production increase for full-year 2026. The sponsor identifies RADAR as an important enabler of alignment around that goal; this forecast is not a completed production result or an increase attributed solely to RADAR.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Innovo Copilot aims to transform business decision-making by bringing AI-powered intelligence directly into SAP Business One. The project enables executives, managers, and department heads to interact with their ERP data using natural language and receive instant insights, reports, comparisons, charts, and dashboards without relying on technical teams. Its key goals are to improve operational efficiency, reduce reporting time, enhance visibility into sales, cash flow, receivables, payables, inventory, and profitability, and identify business risks and unusual trends proactively. With multilingual capabilities, role-based access, and real-time data insights, Innovo Copilot empowers organizations to make faster, smarter, and data-driven decisions. The long-term vision is to make enterprise intelligence accessible, scalable, and practical for businesses of all sizes through conversational AI and intelligent automation.

Innovo Copilot stands out by transforming traditional ERP reporting into a natural, conversational experience. Instead of navigating complex reports, waiting for IT teams, or relying on predefined dashboards, users can simply ask business questions in their preferred language and receive meaningful answers, interactive charts, comparisons, and actionable insights directly from SAP Business One data. Its unique value lies in combining real-time ERP intelligence, multilingual interaction, role-based access, and management-focused analytics in one solution. The platform helps users move beyond historical reporting by highlighting business trends, unusual movements, potential risks, and performance changes to support proactive decision-making. Designed to make advanced business intelligence accessible without requiring technical expertise, Innovo Copilot bridges the gap between enterprise data and business decisions, with the vision to extend AI-powered intelligence.

• Reporting Time Reduction: Reduced routine management reporting time by approximately 70%, from an estimated 30 minutes to 9 minutes per report.

• Improved Productivity: Reduced manual reporting efforts and dependency on technical teams by approximately 60%.

• Faster Decision-Making: Enabled management to obtain real-time business insights through natural-language queries, significantly reducing the time required to retrieve and analyze ERP information.

• Enhanced Management Visibility: Provided faster access to sales, finance, inventory, receivables and other key business performance indicators.

• Improved Accessibility: Enabled authorized management users to interact directly with SAP Business One data without requiring technical or advanced ERP reporting knowledge.

The implementation demonstrates how Innovo Copilot transforms traditional ERP reporting into a conversational, AI-powered business intelligence experience, allowing management to spend less time collecting information and more time focusing on business decisions.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The initiative was launched to bring AI assistance into the bank’s own technology environment, with the controls required for a regulated financial institution: secure deployment, access management, auditability, data protection, and alignment with internal governance standards.

The main objective was to move beyond individual productivity tools and create a scalable platform for AI agents that can support real delivery workflows across the software development lifecycle. By introducing the platform, the company aimed to automate repetitive and time-consuming work, improve consistency and quality of deliverables, and give teams AI support grounded in real project context from systems such as task management, documentation, code repositories, CI/CD, and testing tools.

In short, the objective was to increase engineering productivity by 30%, reduce manual effort, accelerate delivery, strengthen quality controls, and establish a secure foundation for scaling AI across Halyk Bank.

Innovation: The platform is not limited to generic chat or code completion. It supports role-specific AI agents for Business Analysis, Quality Assurance, development, DevOps, code review, release management, onboarding, and future business use cases. Agents work with real enterprise context, generate structured outputs such as user stories, acceptance criteria, test cases, checklists, and automation scripts, and can be adapted by internal teams through reusable templates and no-code/low-code configuration.

Scalability: The solution is designed to run within the bank’s own controlled infrastructure, supporting regulatory requirements, data protection, access management, auditability, and future expansion. It can scale from selected priority use cases to department-wide and enterprise-wide adoption, while allowing different teams to create and adapt agents for their own workflows.

Quantitatively, the target impact includes:

20-40% productivity improvement in selected engineering and QA activities.

Up to 50% reduction in onboarding time for new team members through project-aware AI assistants.

Around 2x cost efficiency improvement in test preparation compared with fully manual test design.

Reduction of 10+ hours of senior engineer time typically spent supporting onboarding and repeated knowledge-transfer questions.

Potential 90%+ time savings in selected document-heavy or policy-checking workflows once the same platform pattern is expanded beyond software delivery.

For external banking clients, the main benefit is improved speed, quality, and reliability of services delivered by the bank. Faster requirements preparation, better test coverage, and more consistent release processes help reduce defects, accelerate digital product updates, and improve customer experience.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Transform employee support by embedding AI into high-volume email and voice channels. The programme aims to automate eligible Global Service Desk requests end to end, improve response and resolution speed, provide always-available conversational support, standardise service quality and release engineers from repetitive work. It also establishes a governed, reusable AI service framework that can be extended to additional enterprise support processes while improving employee experience and operational scalability.

The project combines two distinct AI solutions under one enterprise service transformation: AI-led email fulfilment and conversational voice support. Unlike a conventional chatbot, the model is designed around completed service outcomes. It interprets intent, uses enterprise knowledge, initiates workflows and resolves eligible requests, while routing complex or low-confidence cases to engineers. Its human-plus-AI operating model, multi-channel reach, integration with live service processes and feedback-led improvement create a reusable enterprise capability rather than an isolated automation. The approach has already enabled more than 90% of eligible Global Service Desk mailbox requests to be resolved end to end.

The programme reduces repetitive manual handling, improves responsiveness and expands support capacity without equivalent growth in staffing. Email automation currently resolves 90%+ of eligible GSD mailbox requests end to end. Voice metrics such as interaction volumes, containment, first-contact resolution, handling-time reduction, employee satisfaction and cost benefit must be added after internal validation. The longer-term value is a scalable AI operating model that can be reused across additional enterprise support domains.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Build a Sovereign AI Media OS: Engineer Bluejay-an in-house, model-agnostic agentic engine built from first principles on PydanticAI specifically designed to power Arabic and English newsrooms across SRMG.

Unify Fragmented Workflows: Replace isolated drafting, research, and multimedia tools with specialized AI studio apps and no-code agent workflows that handle end-to-end media operations from research to publishing.

Automate Proactive Intelligence: Deploy background scheduler agents to monitor trends overnight, qualify breaking news, and deliver structured morning briefs to editors.

Embed responsible-AI governance: by design, with explainability, guardrails, mandatory human approval, and a full audit trail.

Maintain Dynamic Cost Control: Implement per-run token and cost tracking across 400+ LLM models to maintain transparent budget management.

The first agentic AI operating system built in-house by a Saudi media group. SRMG engineered its own agent harness on Pydantic AI instead of licensing a vendor chatbot or relying on generic wrappers.

Governance compiled into the engine. Explainability, guardrails, human-review gates, hard stops and per-run cost accounting are built-in runtime primitives, leaving no ungoverned path to publication.

Sovereign and model-agnostic. 400+ models from 10 providers, plus on-premise models for sensitive investigations, switchable at every step, with editorial data kept in SRMG-controlled infrastructure.

One engine, many governed editions. Each publication or desk runs as a configuration of the same platform, with its own isolated agents, tools, models and user experience.

A cultural transformation, not just a tool. Combines platform, agent ecosystem and newsroom adoption to deliver AI speed and scale through human-centered design that safeguards editorial integrity.

 

Operational Scale & Velocity: Generated 13,000+ Al content summaries, processed 10,000+ news feeds, and produced 1,000+ content rewrites with 300+ editor refinements, cutting breaking-news turnaround from hours to minutes.

Ecosystem Integration: Live integration with G.O.A.T app and Billboard Arabia CMS, powering 100% of G.O.A.T app content summaries via Bluejay APIs. 

100% Governed Adoption: Achieved zero ungoverned publication paths; every output passes mandatory human-review gates and maintains full traceability to sources and models. 

Data Sovereignty & Cost Control: Safeguarded embargoed material within SRMG infrastructure using on-premise models while maintaining transparent, per-desk cost attribution across 400+ LLM models.

 

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

To establish a unified corporate AI platform that enables the secure adoption, scaling, and management of artificial intelligence across the company.

Key objectives:

·       Provide employees with fast access to corporate knowledge through AI-powered search and intelligent assistants.

·       Automate repetitive tasks across HR, support, legal, and other departments.

·       Embed AI directly into business processes and corporate information systems.

·       Enable business units to independently create AI assistants and agents without requiring dedicated development.

·       Establish a unified AI Gateway for centralized management of on-premise and cloud-based models, access rights, budgets, and token consumption.

·       Ensure secure AI adoption by developers through Aventa Code.

·       Establish a unified framework for measuring AI performance, including adoption, quality, productivity, and business impact.

Aventa iAventa is an enterprise AI platform combining AI agent development, business process automation, and AI infrastructure management.

Key differentiators:

·       · First in Central Asia: A platform for building enterprise AI agents.

·       · Model independence: Supports local and cloud-based LLMs, enabling selection of the best model for each task.

·       · Agent-first approach: Enables creation of specialized AI agents and reusable Skills, integrated with enterprise systems via APIs and MCP.

·       · Unified AI infrastructure: AI Gateway provides centralized model access, request routing, budget allocation, and cost control.

·       · Security: Supports On-Premise, Cloud, and Hybrid deployment, role-based access control, and local processing of sensitive data.

·       · Aventa Code: Enables secure AI-assisted software development through the corporate AI Gateway.

RESULTS (Q3 2026)

·       3,259 platform users, representing 37% growth over two quarters.

·       Adoption Rate: 86.6%.

·       More than 840 Monthly Active Users (MAU).

·       More than 700 AI assistants created.

·       User satisfaction rate: 84%.

BUSINESS IMPACT

HR: 59% reduction in routine requests (from 164 to 67 per month), saving approximately 9 h. of specialist time monthly.

Contact Center: Automated quality monitoring of 100% of customer conversations, compared to the previous 10% sample-based approach. Review time reduced from 10 min. to less than one minute. More than 65,000 checks completed in September 2026.

Support: Saves 30–45 min. per employee daily; automatically resolves 80–90% of repetitive inquiries; accelerates new employee onboarding by 2–3 times.

Legal: NDA preparation reduced to 5–10 min. from 1–2 h.; up to 30% of routine internal inquiries are resolved automatically.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Create locally hosted computing capacity for AI model training and inference in Kazakhstan. Give businesses, public-sector organisations, researchers and developers access to GPU resources without building their own clusters. Support domestic data storage and processing, reduce reliance on foreign cloud services and provide a platform for internal automation and new digital services.

The project combines a national-scale AI computing cluster with a commercial cloud service and practical enterprise workloads. Users can choose virtual GPU capacity or dedicated bare-metal servers, while data remains hosted in Kazakhstan. The implementation covers both the computing platform and the service layer, including resource access and billing. Its value is demonstrated by deployed contact-centre assistance and procurement-support applications, alongside industry-specific modelling and AI development.

The system achieved 17.93 PFLOP/s in the HPL Linpack benchmark (Rmax), with a theoretical peak of 26.84 PFLOP/s (Rpeak). It ranked 103rd in the November 2025 TOP500 list and 122nd in June 2026.

Operational results include the industrial deployment of the procurement chatbot in 2025 and dozens of hosted projects reported in May 2026, including contact-centre assistance. The platform has also been adopted for power-system modelling, extraction-process optimisation and AI service development.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Prepare the company for a future with many AI agents at work in a regulated, US-listed oil and gas environment, where a data leak or an unchecked failed solution carries legal and reputational cost.

Goals:

1. Know every agent. A central registry holds each agent's objective, owner, guardrails and token limits before it starts working. This replaces inventories compiled by hand.

2. Control access. Deterministic code authorizes every request to APIs, MCP servers and systems against company permission policies.

3. Stop any agent. Every agent exposes a halt callback, so an operator can stop a runaway or compromised agent from one control room.

4. Monitor consumption. Tokens are tracked by day, week, month, quarter and year, with alerts near limits.

5. Stay independent of any model vendor, so governance works with any platform.

Status, October 2026: ACT and Ground Control are built and operating.

Governance implemented as running code. The policy lives in two services that apply it to every agent in real time.

The Agent Control Tower (ACT) is a REST API where agents register, report progress and can be halted. Ground Control is deterministic code that authorizes access to resources and issues temporary tokens. An agent never judges its own access, and only an agent registered in the tower receives a list of resources.

The design works with any agent technology. It runs through MCP servers and API calls, so custom GPTs, skills, plugins and agents coded with model APIs and agent-to-agent architectures can all join.

The model borrows from air traffic control: the tower knows every plane and can order it down, and ground control decides which gates each plane may use.

Halting is part of the protocol: every agent exposes a halt callback to register.

October 2026. ACT and Ground Control (since September) are operating. Five people delivered them between June and October: a tech lead, an architect, two developers and the head of AI.

Readings: 4 agents are registered in ACT. ACT audits about 37 events per day. Ground Control recorded 23 access denials in its first two weeks. The live registry replaces manual inventories.

Roadmap: durable access logging in Ground Control, registration of every agent by December 2026, migration of GPTs to skills and plugins, and testing the protocol for user GPTs and skills. It is written as a company-wide skill, and Halt sets a user's usage availability to 0 or deactivates the user through the enterprise management console API.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The goal of the Save Plus project is to streamline and digitize customer loyalty and promotional activities by integrating business processes with Microsoft Dynamics 365 Finance & Operations. The project aims to improve customer transaction tracking, automate relevant account and procurement processes, enhance data accuracy, and provide centralized reporting for better business decisions. It also focuses on improving coordination between Accounts, Procurement, IT, and retail operations, reducing manual work, strengthening operational controls, and establishing a scalable system to support Save Mart’s customer engagement and retail growth.

The uniqueness of the Save Plus project lies in integrating customer-focused retail operations with Microsoft Dynamics 365 Finance & Operations to establish a centralized and streamlined business process. The solution aims to connect customer transactions, account management, procurement activities, and reporting while improving data accuracy, transparency, and operational control. It supports automation of manual activities, standardization of business workflows, and improved coordination between departments and retail stores. The project provides a scalable foundation for enhanced customer engagement, efficient retail operations, and data-driven decision-making across Save Mart.

The Save Plus project established an integrated operational framework for flour and rice processing, packaging, inventory management, and distribution to Save Mart retail stores using Microsoft Dynamics 365 Finance & Operations (D365 F&O). The solution improved visibility of raw materials, processed products, packaging materials, and finished goods while supporting more accurate inventory tracking and stock reconciliation. It streamlined purchase order processing, vendor management, warehouse operations, store replenishment, and financial reporting. The project also strengthened cost monitoring by improving the tracking of procurement, transportation, packaging, and processing expenses. Overall, Save Plus supports better coordination between procurement, accounts, warehouse, production-related operations, and retail stores, helping improve supply chain efficiency, inventory control, product availability, and management decision-making.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Project CORTEX - Powering the Core of Textile Excellence is Artistic Milliners enterprise-wide digital transformation program, designed to create a connected, AI-enabled and data-driven digital backbone for a complex, vertically integrated textile and apparel business spanning Pakistan and the Western Hemisphere.

The program is transforming a decade old Oracle E-Business Suite (EBS) landscape into a unified, cloud based ecosystem for complex, multi-company and multi-location environment powered by Oracle Fusion Cloud ERP, SCM, HCM, Product Management, Plant Maintenance, Manufacturing, analytics, automation, and AI-driven capabilities.

CORTEX combines a large-scale extends beyond a conventional ERP transformation. It is focused on reimagining how the organization operates and makes decisions. Standardized processes, stronger governance, real-time information, integrated data and emerging AI capabilities are enabling greater visibility, faster decision-making, improved controls and operational agility across business divisions. The program is progressively introducing "AI agents and intelligent workflows" to enable faster decision-making, automate repetitive activities, identify exceptions, improve forecasting and provide business users with contextual insights directly within their operational processes.

Ultimately, Project CORTEX is building the digital nervous system of Artistic Milliners by connecting people, processes, data and intelligence across continents and establishing a scalable technology foundation for the company's next generation of textile excellence, sustainable growth and AI-enabled innovation.

From an operational perspective, integrated SCM, Manufacturing, Plant Maintenance, Inventory and Product Management capabilities provide improved visibility into materials, inventory, equipment and production processes. This creates the digital foundation for better resource utilization, optimized inventory levels, reduced process waste and more effective preventive maintenance.

CORTEX also strengthens the organization's ability to capture, govern and analyze sustainability-related data across companies, manufacturing locations and geographies. Integrated data, analytics and AI capabilities can increasingly support management in identifying inefficiencies, monitoring resource consumption and incorporating sustainability considerations into operational decision-making.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

AI assitant for Banks DWH based on data catalog and business glossary.

To grant bank employees direct access to corporate data warehouse information, eliminating the need to consult with analysts or IT staff. The objectives are: (1) to develop an AI assistant capable of interpreting natural-language queries to locate relevant data, explain its meaning, generate the corresponding SQL query, and execute it within the data warehouse; (2) to ensure the accuracy of responses by relying on a defined data model and business glossary, rather than the AI ​​model’s internal "knowledge"; (3) to adhere to banking security requirements by ensuring the model operates within the bank’s secure environment, respects user access permissions, and is restricted to read-only operations; (4) to accelerate the migration of the data warehouse to a new platform by automating the rewriting of report queries; and (5) to engage business stakeholders in defining their own metrics and terminology.

The assistant doesn’t guess—it relies on data descriptions. Every response is built from three sources: the data warehouse model, the technical catalog, and the business glossary. This drastically reduces the risk of hallucinations: the model doesn’t invent tables or metrics; instead, it locates them within these descriptions. The technical documentation was prepared by data specialists, while business terms and metrics were defined by the individual departments—essentially, the entire bank.Catalog has become a practical working tool rather than just a formality; the quality of the assistant’s responses depends directly on the quality of the catalog itself. The solution operates entirely within the bank’s internal environment using an open model; it is integrated with the directory service and access control system, functions in read-only mode, and includes a request-validation checkpoint before any action is executed.

The assistant proved valuable beyond just the business side: during the migration of the storage layer to a new platform, it enabled a team of two people to re-map over 4,000 reports in just three months—a task that otherwise would have required six people working for an entire year.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The objective of this project is to extract relevant sales, receivables, and inventory data from SAP and present it through a centralized, user-friendly dashboard. The solution will provide division-wise sales performance, outstanding balances, invoice ageing, and fast-moving and slow-moving item analysis to support better business decisions and operational efficiency.

The uniqueness of this project lies in integrating division-wise sales, customer outstanding, invoice ageing, automated email reminders, and fast-moving/slow-moving inventory analysis into a single, user-friendly dashboard. Users can drill down from division-level summaries to customer names and individual invoice details through interactive icons without logging into SAP. The solution reduces dependency on manual reporting, simplifies payment follow-ups, improves visibility into overdue receivables, and helps identify high-demand, slow-moving, and non-moving items. By combining financial and inventory insights in one platform, the project enables faster decision-making, better inventory planning, improved collection efficiency, and enhanced operational control.

The project has significantly improved the efficiency and accessibility of business reporting. Earlier, generating and consolidating the required SAP reports took at least 10–15 minutes every week and involved dependency on backend users for information retrieval. With the implementation of this solution, reports and detailed information are now readily available at users' fingertips, eliminating repeated backend requests and manual report preparation. Approximately 10–15 stakeholders benefit from direct access to division-wise sales, outstanding balances, customer details, invoice ageing, and inventory movement reports. The invoice-level drill-down, email reminder facility, and fast-moving/slow-moving item analysis have streamlined financial monitoring, payment follow-ups, and inventory tracking. The solution saves at least 10–15 minutes per weekly reporting cycle, reduces operational dependency, and enables faster, informed business decisions.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Halyk BaaS is a strategic platform from Halyk Bank designed to make banking, ecosystem, and government digital services accessible to customers exactly where they already are—within the mobile applications they use daily. The primary goal was to build a unified technological platform that would eliminate the need for bespoke, one-off integrations with individual partners, shifting instead to a scalable connection model based on a single SDK and API. This approach has significantly reduced integration complexity, accelerated the time-to-market for new services, and laid the foundation for the rapid expansion of the partner network. The core objective was to create a platform that would allow partners to enhance their own digital products by incorporating in-demand financial, ecosystem, and government services—all while maintaining a seamless, unified customer journey within the partner’s own application. Today, Halyk BaaS connects partners with a combined customer base ~500,000 users.

Halyk BaaS creates value not only as a technological platform but also as a new digital distribution channel for banking services, enabling Halyk Bank to scale its financial capabilities through an ecosystem of partners. At the core of the platform is the principle of integrating banking services into the digital workflows that users already engage with. Instead of requiring customers to visit a dedicated banking app, Halyk Bank allows its services to be accessed directly within partner applications, ensuring a seamless user journey. This approach transforms the interaction model between the bank, its partners, and its customers. Customers gain access to services exactly when they need them, without the need to switch between different applications. Users can pay a restaurant bill, purchase an event ticket, apply for a bank card, obtain a loan, or utilize a loyalty program—all from within a partner’s app. This significantly shortens the time-to-market for new digital products.

Halyk BaaS created a new revenue stream for Halyk Bank,confirming the market demand for the platform.

TAS Finance,a microfinance organization for microloans secured by vehicles and real estate.Loan disbursements:4,334 transactions (KZT 9.63 billion).Loan repayments:685 transactions (KZT 143.68 million).

ONAY! is the largest electronic ticketing system for public transport in Kazakhstan, used for issuing transport cards for various categories of citizens.BaaS issues discounted transport cards for schoolchildren and pensioners.

Vlife-platform for motorists that integrates loyalty programs,fuel payments,electric vehicle charging, and other partner services(6,342 QR trns;42.32 mln KZT)

Altyn Bank integrated External QR Pay service,allowing clients to pay via Halyk QR directly in Altyn Bank app(40,742 QR trns;434.24 million KZT)

WOOPPAY-provides an e-wallet,internet acquiring, and digital payments.BaaS enables users to pay via Halyk QR directly from the WOOPPAY(1,889 QR trns;3.81 mln KZT)

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Turn RPA into a strategic in-house automation platform: scale automation of banking operations without growing the back office and without vendor lock-in. Goals: complete the migration of the platform to an in-house, fault-tolerant open-source stack with zero license fees; adopt an open-source workflow orchestration engine as the target core for robots and end-to-end processes; grow the portfolio to 100+ robots in production; make routine operations 10+ times cheaper than manual processing with payback within six months; cut robot development time to 2–3 weeks; embed locally hosted AI models within the bank's perimeter so robots can handle scans, documents and free text; build the RPA developer profession inside the bank.

The AI Empowered RPA platform is built entirely in-house instead of a commercial RPA product — zero licenses and over $1M in annual savings versus an off-the-shelf solution. A robot is software code with full engineering practices: repository, CI/CD, monitoring, logging. Temporal, approved by the bank’s Architecture Committee as the target orchestration core, turns robots into durable workflows: each step is persisted, failures are retried automatically and long-running processes survive restarts. Robots scale in days: when volumes grew tenfold and more, 4 robots were added instead of hiring about 40 employees. AI models run locally inside the bank’s perimeter: customer data never leaves for external clouds, and high-risk decisions remain with people.

100+ robots in production across operations, lending, finance, compliance and IT/HR; up to 7x higher throughput in automated processes; the same workload handled 10+ times cheaper than manually from the second year; payback within six months; a vendor-independent, fault-tolerant platform with an approved target orchestration architecture.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The strategic goal was to eliminate manual routines, dismantle data silos, and accelerate decision-making across back-office, legal, procurement, finance and customer service units.

Key Delivered Modules:

• Intelligent Document Processing (IDP): Zero-touch extraction, cross-validation, and multi-system entry for complex documents with near-zero error rates.

• Corporate Knowledge Base (RAG/LLM): Enterprise semantic search delivering instant, verified internal guidance and SOPs directly to frontline specialists.

• Conversational BI & Predictive Pricing: An executive reporting assistant for natural-language business queries, paired with an ML model for dynamic asset valuation.

• AI-Augmented Customer Engagement: Telephony speech analytics, automated CRM ticket routing, and personalized outbound sales communications.

Strategic Impact: Create a lean, high-ROI cognitive automation ecosystem driving labor productivity and measurable top-line growth.

The standout innovation of this initiative lies in the synergy between robust deterministic RPA and cognitive Generative AI within a unified enterprise architecture. Instead of deploying isolated basic scripts, the solution is powered by a dedicated fleet of software robots running several mission-critical automated scenarios, seamlessly orchestrated alongside cutting-edge LLMs, RAG pipelines, and ML models.

Unlike traditional point-tools, this ecosystem natively connects disparate legacy environments with core platforms (SAP ERP, proprietary CRMs, DMS and commercial portals) across international branches. This hyperautomation loop delivers dual impact:

• Operational Excellence: Complete elimination of manual processing backlogs and human data-entry errors.

• Top-Line Revenue Acceleration: It transforms automation from a cost-cutting tool into a commercial driver via automated real-time catalog repricing, frictionless cross-border B2B logistics and automated personalized customer offers.

The project delivered measurable operational, financial, and strategic impact:

• Labor & Resource Savings: Reclaimed recurring capacity equivalent to several dozen FTEs monthly. Routine paperwork fell by 30–70%, while back-office productivity surged by >40%.

• Operational Velocity & Accuracy: Document processing accelerated by 5–20x with near-zero errors. Dynamic commercial catalog repricing turnaround was slashed from days to 2–3 minutes.

• Commercial Growth & Service Quality: Frontline teams retrieve verified SOPs 10–30x faster with 97%+ accuracy. Automated personalized outreach boosted lead capture by 5–10% and transaction values by 5–15%.

• Strategic Governance: Natural-language analytics compressed executive reporting cycles by 5–15x, empowering leadership with real-time operational visibility across regional hubs.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Solis Data Manager (SDM) is a data management platform built on the DAMA-DMBOK framework to solve data quality, ownership and accessibility problems at Solis Investimentos. Using big data technology, SDM delivers trusted, near real-time information to business teams, enabling faster and more reliable decisions in a regulated financial environment.

SDM creates a single, governed foundation for corporate data. It applies DAMA-DMBOK practices, including [data governance, data quality, metadata management], with clear ownership by business domain and governance built into data delivery rather than added afterwards.

The platform is designed to scale across domains and use cases, laying the groundwork for advanced analytics and responsible AI adoption.

SDM is unique because it combines two things that are usually delivered separately: formal data governance and real-time big data delivery. Most initiatives either start with technology and add governance later, or define governance frameworks that never reach the speed the business needs. SDM brings the DAMA-DMBOK standard directly into the data pipeline, so ownership, quality rules and business definitions are applied as data flows, not in after-the-fact reviews.

As a result, business teams get information that is both fast and trusted, from a single governed source, instead of having to choose between speed and reliability.

[Add only what is true: built in-house by a team of X / designed for Brazilian regulation (LGPD, CVM, BACEN) / automated quality rules / integrated business glossary / AI-ready foundation.]

Since its launch, SDM has transformed how Solis uses data. Report delivery time dropped from 5 days to 30 minutes, while 10% of critical data elements now have a defined owner and business definition. Automated quality rules cover [N] datasets, raising data quality scores from 10% to 20% and cutting manual reconciliation effort by 100 hours per month. 10 business areas and 100 users now access governed data through a single platform, and 100 dashboards and APIs run on SDM data. Decisions that once relied on end-of-day or end-of-week reports are now supported by information refreshed every 30 minutes. Beyond efficiency, SDM strengthened regulatory readiness through [lineage and audit traceability for LGPD/CVM/BACEN reporting] and prepared Solis for responsible AI adoption, with 10 use cases already planned or in development.

— The project does not use solutions from the Global CIO catalog

— Profile «BPMSoft» in the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— Profiles of «BPMSoft», «Colvir Software Solutions» in the Global CIO catalog

Fix the root cause of a large share of delivery failures: poor address data. Addresses arrived from many different shippers in inconsistent formats, with no method to interpret, standardize, consolidate or correct them. This caused 7% delivery non-conformity, re-delivery and return costs, 14% more customer service tickets and a loss in on-time delivery (SLA). Goals: (1) build an in-house engine that validates, standardizes, enriches and geocodes every address before routing; (2) raise on-time delivery and cut customer complaints; (3) make routing more accurate and reduce operating costs; (4) replace expensive third-party address tools with a low-cost, serverless solution; and (5) design it so it can later be offered to the market as an address-treatment service.

Instead of buying an address-cleansing tool, the IT team built its own engine and cut tooling cost from R$ 40,000 to about R$ 100 a month. The design is hybrid and cost-aware. A library of hundreds of deterministic functions validates, standardizes and consolidates addresses, using business rules each shipper can configure and proprietary enrichment bases built from the company's own delivery history. A large language model is called only for the exceptions rules cannot solve: splitting free-text addresses into attributes, finding the house number, classifying ambiguous cases. Each corrected address also receives precise coordinates, so routing improves as well as the record. Everything runs on serverless, event-driven components, so cost follows volume. The engine was designed from day one to be productized as an address-treatment service for other companies.

Results. On-time delivery (SLA) up from 95% to 96%; customer complaints down 5%; more accurate geocoding and routing, fewer re-deliveries and lower operating costs; third-party tooling cost cut from R$ 40,000 to about R$ 100 a month (-99.7%).

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aimed to transform the organization's global wide area network into a secure, scalable, and sustainable SD-WAN platform supporting business growth, operational resilience, and digital transformation. The program sought to replace legacy network architectures with a centralized, policy-driven connectivity framework that enhanced application performance, improved user experience, strengthened security, and simplified network management across multiple countries. Key objectives included increasing network agility, reducing operational complexity, supporting cloud adoption, enabling rapid onboarding of sites, improving visibility and governance, and establishing a future-ready foundation for business operations. The program also supported sustainability initiatives by optimizing network resources, reducing dependency on legacy infrastructure, and enabling more efficient utilization of digital services across the enterprise.

The uniqueness of this project lay in delivering a multi-country SD-WAN transformation while maintaining uninterrupted business operations. Beyond a traditional network refresh, the program established a repeatable global transformation framework integrating governance, stakeholder engagement, risk management, supplier coordination, and phased migrations. It successfully balanced regional requirements, varying infrastructure maturity, and business-critical needs while driving standardization across global locations. The initiative emphasized sustainability, operational efficiency, resilience, and future readiness. By creating a scalable and reusable delivery model, the project accelerated digital transformation, strengthened connectivity, and provided a foundation for future enterprise modernization initiatives.

The project successfully transformed the enterprise connectivity landscape through the deployment of a standardized global SD-WAN platform. The initiative improved network agility, operational visibility, application performance, and overall service resilience across multiple business locations. Centralized management simplified administration and accelerated the onboarding of new sites and services. The transformation strengthened security, supported cloud adoption, and enhanced the user experience through optimized traffic routing and improved reliability. The program established a scalable and sustainable network foundation capable of supporting future digital initiatives. In addition, a repeatable delivery framework, effective stakeholder management, and strong governance practices enabled successful execution while maintaining uninterrupted business operations throughout the transition.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

• Build a Robust, Next-Generation Security Architecture: Leverage advanced and emerging cybersecurity solutions to strengthen the security posture of critical National Grid infrastructure.

• Ensure End-to-End Security Coverage: Establish comprehensive protection across users, servers, cloud environments, and Operational Technology (OT) through an integrated security framework.

• Enable 24×7 Security Monitoring and Response: Implement continuous threat monitoring, intelligent detection, and timely response to proactively identify and mitigate cyber risks.

• Safeguard Data and Ensure High Availability: Strengthen data confidentiality, integrity, and availability while enhancing infrastructure resilience.

• Ensure Business Continuity: Minimise security-related disruptions and enable safe, reliable, and seamless business operations across IT and OT environments.

The project’s uniqueness lies in establishing a comprehensive, resilient, AI-enabled IT-OT cybersecurity architecture for Solar, Wind, and BESS operations. It integrates Palo Alto SASE/GlobalProtect, Cortex XDR Pro, XSIAM with Managed SOC for 24×7 monitoring and response, Check Point Harmony Email Security, and dedicated Palo Alto IT and Fortinet OT firewalls. Veeam protects servers, email, OneDrive, and SharePoint, while Acronis safeguards SCADA systems. Microsoft Entra ID and Intune MDM enable identity-centric access control and endpoint governance, complemented by HPE Aruba switches and access points with Entra ID-based authentication. This integrated, defence-in-depth approach strengthens threat prevention, data security, IT-OT resilience, recovery readiness, and uninterrupted renewable energy operations.

Implemented a resilient, integrated IT-OT cybersecurity ecosystem across Solar, Wind, and BESS operations. AI-enabled threat detection, 24×7 monitoring, and managed incident response enhanced threat visibility and response readiness. Dedicated IT and OT firewalls strengthened network segmentation and SCADA protection. Advanced email security, secure remote access, identity management, and endpoint controls improved protection across users, devices, and enterprise resources. Veeam and Acronis backup solutions strengthened data protection and recovery preparedness across enterprise IT, Microsoft 365, and SCADA systems. This defence-in-depth architecture established a scalable security foundation, strengthened cyber resilience, reduced exposure to evolving threats, and enhanced business continuity to support reliable and uninterrupted renewable energy operations.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

1. Achieve real-time, location-level inventory accuracy using RFID-based pallet tracking and QR-based product tracking.

2. Digitize all warehouse operations (receiving, put-away, picking, dispatch) through mobile apps that guide workers and capture every movement.

3. Provide a live 2D virtual warehouse showing stock position, capacity, and utilization.

4. Enable end-to-end traceability, so any product or batch can be traced from production through storage and dispatch to market.

5. Integrate with the ERP system so stock, orders, and financial records update automatically without double entry.

6. Reduce loading and dispatch time, mis-shipments, stock-outs, and expiry losses.

7. Support FEFO and batch controls, and strengthen recall readiness and audit compliance.

Warehouse Connect combines several technologies that are usually bought separately and rarely integrated well.

• RFID at the center: Pallets carry RFID tags that are read automatically at gates and on forklifts, so movements are captured without scanning or manual entry.

• Two-layer identification: RFID tracks pallets while QR codes track individual cartons and units, giving traceability at both levels.

• Live 2D digital warehouse: The physical warehouse is mirrored virtually, with every pallet shown at its real location.

• Consumer-to-warehouse traceability: Through a mobile app, a product in the market can be traced back to its batch, production, and storage history.

• Native ERP integration: Stock and order data synchronize with the ERP in real time.

• Built for local conditions: It is built in-house and works with mixed layouts, intermittent connectivity, and limited IT staff, at a fraction of the cost of global WMS suites.

• Inventory accuracy improved from 88% to 99.5%

• Pallet search and stock-count time reduced by 88%

• Dispatch and truck-loading time reduced by 47%

• Mis-shipments reduced by 71%

• Expiry-related stock losses reduced by 40%

• Manual paperwork and double data entry eliminated

• Estimated payback period: 12 months

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

At the core of Qiddiya’s vision is an advanced, unified observability hub that operates proactively in support of its strategic objectives. With a landscape of multiple clouds, PaaS and SaaS platforms and a data center serving offices and a growing number of asset sites, a command center was essential to growth and operational excellence. The objectives were to:

●        Availability: maintain 24x7 availability of all IT, OT and IoT systems, including key services, applications, infrastructure and network.

●        Unified monitoring: implement an advanced, unified IT/OT/IoT monitoring hub, the Intelligent Command Centre (ICC), to support corporate goals proactively.

●        Full-stack coverage: monitor applications, databases, messaging, middleware, virtual systems, cloud, servers, network and every other IT/OT/IoT element.

●        Visibility and efficiency: achieve high visibility, faster issue resolution and greater efficiency for smooth operations and excellent service.

A command center designed to grow with a city. [AF1] The ICC started with corporate IT and was built from day one to extend to every asset, office & smart system the destination adds. New theme parks, venues and offices join one command view as they open, rather than each bringing its own monitoring solutions.

Four observability domains (infrastructure, applications, cyber security, and OT/IoT smart solutions) come together on one platform that acts as a manager of managers: a single pane of glass, linked directly to service management and automation.

Onboarding is measured, not negotiated. Each application is scored for readiness & given one of four paths (ready, adapt, re-architect, or replace), so critical systems do not go live unobserved.

AI-driven anomaly detection, event correlation and root cause analysis move operations from reactive to proactive, on a roadmap to predictive, self-healing operations. A center of excellence & a Saudi graduate fellowship keep the capability growing

In 2026, the focus moved from building to running. Structured knowledge transfer covered five monitoring platforms, followed by a 45-day operational takeover with readiness gates. Since 1 October 2026, the ICC has run as a 24x7 managed service, combining an on-site team in Riyadh with remote engineering teams, while a fellowship of 12 Saudi graduates trains to operate it.

The roadmap now takes the ICC from managed to predictive operations, linking business KPIs to technical metrics and adding automated root cause analysis and self-healing infrastructure as more of the city comes online.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Entering a new sales order meant reading the customer purchase order (a PDF with a different layout, language and terminology for every customer) and typing each line into the ERP by hand: quantities, prices, discounts, delivery dates, destinations, customer tags and item numbers. Above all, the operator had to identify the right internal article among thousands of flange codes. The work was slow, repetitive and error-prone, and errors spread to production, purchasing, quality documents and shipping. Objectives:

• let order-entry staff upload the customer PO and have all order lines created automatically in the ERP;

• automatically propose the internal article by interpreting the technical description;

• keep the operator in control, with clear flags on lines that need a check;

• reduce order-entry time and data-entry errors, freeing staff for higher-value work.

The hard part is not reading a PDF: it is turning free-text technical descriptions written by hundreds of different customers into the exact internal code of a forged flange. The solution combines a large language model with a domain rule engine. The model extracts each line and its technical attributes (standard, rating, nominal and reduction diameters, schedule, geometry, facing, finished or raw, special processing). The engine then maps them to the article master data, including material equivalences (e.g. UNS codes vs. ASTM grades) and customer specifications.

For each document they import, users can add one-off rules in natural language, which are combined with the rules already defined in the system for that import only, with no per-customer templates to maintain. Lines without a certain match are flagged and resolved in one click; a ground-truth set of real orders measures accuracy at every model or rule change.

Results: order lines are no longer typed one by one, and the operator moves from data entry to review. Errors on quantities, prices and dates drop, and the same procedure works for any customer layout without per-customer templates.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

AXS Energia is a Brazilian energytech founded in 2021 with no legacy systems and one premise: treat data as core business infrastructure from day one. The company sells solar energy by subscription and operates its own distributed generation fleet, delivering one to two new plants per month. The goal was to grow at this pace without losing control: unify plant telemetry, IoT sensors, SCADA, weather stations, ERP, CRM, finance, maintenance and connections to more than ten utility distributors in a single operational layer; move decisions from individual experience to history, patterns and integrated data; and solve a sector-specific problem, the cold start: machine-learning forecasting models need about three years of history, and a fast-growing fleet always has new plants without it.

Orion is not an AI layer bolted on later: AXS was born without legacy systems, and Orion is the direct consequence of treating data as infrastructure since day one. The intelligence layer runs on InterSystems IRIS with a data fabric architecture and four analysis pillars (descriptive, diagnostic, relational and predictive). Vector search relates current events to operational history, automatically identifying similar anomalies and standardizing O&M responses. The signature innovation is a physics-based photovoltaic digital twin (pvlib, embedded Python inside IRIS) that writes, with the laws of physics, the history a new plant does not yet have: in a proof of concept validated against 208 days of real generation, it reached 81.68% baseline forecasting accuracy on the plant's first day, rising above 92% as real data accumulates. On top of this foundation, Ask ORION brings generative AI that answers from Orion's own data, not from model assumptions.

Published 2025 indicators: OPEX per installed MWp down 38% (reflecting Orion and scale gains), mean time to diagnosis down 32%, MTTF up 27%, and above 92% accuracy in generation forecasting; forecasting results (92% and 81.68%) were measured jointly with InterSystems. Customer and environmental impact in 2025: about R$ 144 million in direct savings for customers and about 83,000 tonnes of CO2 avoided, serving more than 33,000 customers, growing toward 50,000, with waiting lists for new plants. Scale: 72 plants in operation across five Brazilian states, heading to 130 plants and 335 MWp, with one to two new plants delivered per month. Net revenue grew from R$ 53 million to R$ 100 million in one year (88% growth, independently audited). The case was presented at InterSystems READY 2026 (Washington, DC), at Intersolar South America 2026 and at a data & AI roundtable at the Gartner CIO & IT Executive Conference 2026.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

1. Build a live digital twin of equipment, production facilities, and maintenance processes in a single platform.

2. Replace fragmented spreadsheets and paper logs with one CMMS as the source of truth for asset health, history, and cost.

3. Move maintenance from reactive and calendar-based to condition-based and predictive.

4. Forecast failures, spare-part demand, and maintenance workload before they disrupt production.

5. Run “what-if” simulations to optimize maintenance schedules, resource allocation, and facility performance.

6. Reduce downtime and maintenance cost while extending asset life and improving safety and compliance.

7. Create a scalable platform that can be rolled out across plants and industries.

Most CMMS products are systems of record, and most digital twin tools are visualization layers sold separately. Assets Connect unites both: the twin is the working maintenance system, not an add-on.

• Each asset has a living digital model that links its hierarchy, live condition data, maintenance history, spare parts, and cost in one view.

• Forecasting and optimization run directly on that model, and results feed straight into work orders and planning.

• It was designed for the realities of emerging-market industry: mixed legacy and modern equipment, intermittent connectivity, and limited specialist staff. Deployment is fast and does not require ripping and replacing existing machinery.

• It was built in-house with an integration-first architecture, so it connects to ERP, SCADA/PLC, and IoT sources without vendor lock-in.

• AI-based failure prediction, mobile/offline work orders, QR/RFID tagging

• Results measured estimated six months pilot period against the prior baseline:

  • Unplanned downtime reduced by 22%

  • Maintenance cost reduced by 13%, with preventive maintenance compliance rising from 45% to 72%

  • Mean time to repair reduced by 23%

  • Asset availability up from 86% to 94%

  • 11 potential failures flagged and resolved before they caused stoppages

  • Spare-part inventory optimized, freeing PKR 15 million in working capital

  • Paper-based maintenance processes eliminated at the pilot facility

  • Estimated payback period: 14 months; estimated annual savings: PKR 20 million

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Complete the end-to-end digital conversion of a listed closed-ended investment fund into an open-ended fund, enabling subscription, redemption and ongoing investor servicing. Migrate the holdings of approximately 60,000 unitholders while preserving recorded ownership and meeting critical regulatory milestones. Remove the need for every investor to have an existing CRM account at conversion by registering units against investor identity references. When an investor subsequently registers, completes KYC and activates an account, automatically link their previously registered units. Establish a scalable and controlled model for fund operations and digital investor access.

The defining innovation was an identity-first ownership architecture that decoupled fund-unit registration from customer onboarding. Unlike conventional account-dependent migration approaches, the solution could register existing investment holdings using an investor identity reference without requiring a CRM profile. When an investor subsequently completed KYC and activated an eligible account, the previously registered units were automatically linked to it. This removed a critical dependency in migrating approximately 60,000 unitholders, reduced the need for simultaneous mass onboarding, and separated ownership continuity from customer-service eligibility. The approach provides a reusable model for large-scale, regulated investment-product transformations.

Successfully completed the end-to-end digital conversion of a listed closed-ended investment fund into an open-ended investment model, migrating and reconciling 60,000 unitholder records. Of these, 59,000 holdings were registered using investor identity references without requiring existing CRM accounts, eliminating mass onboarding as a prerequisite for conversion. Following KYC completion and account activation, 6,000 successful automatic unit-to-account linkages were achieved. The new operating model also successfully processed 8,000 subscription and redemption transactions after conversion. These measurable outcomes demonstrate large-scale ownership continuity, operational automation, investor adoption and a scalable digital investment-servicing model.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Halyk Bank’s FacePay project has been launched in the Almaty Metro and the Astana Light Rail Transit (LRT) system. The primary objective of the FacePay launch was to introduce an innovative, convenient, and secure payment method, enabling customers to make payments without the need for bank cards, cash, or mobile devices. The project was aimed at advancing digital and biometric technologies, enhancing the speed and convenience of customer service, reducing transaction times, expanding cashless payment options, and further strengthening Halyk Bank’s position as a leader in the digital transformation of Kazakhstan’s financial sector.

The first use case for the service was paying for rides on the Almaty Metro using facial recognition technology, which allowed passengers to pass through turnstiles without needing to present a bank card, smartphone, or transit ticket. Then it was scaled to LRT Astana and regular merchants

The value proposition of FacePay lies in providing customers with an exceptionally fast, convenient, and secure payment method based on biometric identification, which completely eliminates the need for a bank card, cash, or a mobile device.

The key distinction of FacePay compared to similar solutions on the market lies in the integration of biometric payment directly into the bank’s ecosystem and its application in common, everyday scenarios. The service provides a seamless user experience, reduces the time required to complete payments, and lessens the customer’s reliance on physical payment instruments. It has helped address the issue of queues at turnstiles and increased the throughput capacity of metro stations.

In terms of innovation, this project represents one of the first large-scale banking solutions in Kazakhstan to use facial recognition for payments—initially implemented within transport infrastructure and subsequently adapted for other payment scenarios.

FacePay has significantly enhanced payment convenience for customers and has been made available to Halyk Bank’s extensive user base, which includes over 11.5 million active bank clients and more than 8.5 million monthly active users of its Super App. It enables passengers to pay for rides on the Almaty Metro and Astana LRT using biometric facial recognition and reduces reduced queues on the stations during peak hours. To make a payment, customers no longer need a bank card, smartphone, cash, or a QR code—only to complete a one-time registration process within the Halyk mobile app.

Key benefits for customers:

1. an exceptionally fast, contactless payment method for millions of customers

2. shorter transit times through turnstiles and greater convenience for 11.5 million active bank customers

3. no need to carry a bank card or phone when using the service

4. a high level of security, ensured by biometric authentication

5. a modern and seamless user experience for those using the Super App

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

1. Create a convenient ecosystem for digital asset holders, enabling them to use wallet funds for everyday purchases through HUMO, Visa and Mastercard, including contactless and online payments, as well as cash deposits and withdrawals.

2. Enable remote customer onboarding with identity verification (KYC), virtual card issuance, physical card ordering, collection through card-issuing kiosks and activation in the app without visiting a bank branch.

3. Establish direct settlement with Visa in USDC to ensure same-day receipt of funds without intermediary banks and enable more responsive liquidity management.

4. Integrate digital wallets with the bank’s processing system to support card transactions using crypto assets.

5. Adapt banking processes to digital asset transactions in accordance with the regulator’s requirements.

1. Direct settlement with Visa in USDC. Octobank became the first bank in Central Asia to transition to direct settlement with Visa in USDC.

2. Banking products powered by crypto assets. Octobank became the first bank in Uzbekistan to launch a suite of banking products using crypto assets: cards, acquiring, payments and transfers.

3. A distinctive onboarding and product issuance system. A unified customer journey combines identity verification, digital product applications, physical card ordering, collection through card-issuing kiosks and activation in the app without visiting a bank branch.

1. Established a digital asset banking ecosystem with HUMO, Visa and Mastercard cards for contactless and online payments, plus cash-in/cash-out.

2. Enabled remote KYC, card applications, physical card ordering, kiosk issuance and in-app activation without visiting a branch.

3. Implemented direct Visa settlement in USDC. The bank received 100,000 USDC during the reporting period. Funds arrive the same day, averaging 15–20 minutes after the final settlement amount is determined, versus 1–10 business days previously.

4. Integrated digital wallets with bank processing to check available funds during authorization, without prior transfers to a separate bank account.

5. Adapted banking processes to regulatory requirements, automated settlement requests, reconciliation and monitoring, and updated accounting, operational support and the contractual framework.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Turn Daman Markets, a UAE broker with roots going back to 1998, into a Brokerage-as-a-Service (BaaS) provider. Banks, fintechs, digital wallets and super apps can then offer trading inside their own apps without building or licensing a brokerage. The goal is to let any regulated institution add an "Invest" button, backed by Daman's trading technology, liquidity, onboarding, compliance tooling and back-office operations, through a single integration. The customer stays in the partner's brand and journey; the partner keeps the relationship and gains a new revenue stream; Daman's licensed entities remain the broker of record. The longer-term goal is a scalable, measurable B2B business line that serves many partners on one standard platform and is designed so it could later operate as an independent company within the Daman group.

Most brokers expand by acquiring retail customers one at a time or by redirecting users to a separate trading app. Daman Embedded Trading reverses this. Trading is embedded inside the partner's own app through a modular, Kotlin-based SDK and APIs, with single sign-on so the customer never creates a second login. Partner data is reused with consent, so customers answer only the brokerage questions. Partners choose from three integration patterns (full SDK, hybrid, API-only), three onboarding models, three branding models and several funding models, including transfers from the partner's own accounts or wallet. Behind the technology sits an operating model built for regulated reality: every partner is routed to the correctly licensed booking entity, and Compliance holds an independent veto at each approval gate. The result is a configurable platform, not a bespoke build per partner.

The programme has completed the core design of the business. Delivered so far:

• A full product proposition and partner-facing presentation.

• An SDK and API architecture with three integration patterns.

• A Kotlin-based SDK with modular components.

• Defined onboarding, funding, branding, support and commercial models.

• A business-line operating model with a seven-gate partner lifecycle, booking-entity routing, governance forums and a 24-month roadmap.

The commercial pipeline is active: the first institutional partner, a listed West African universal bank, has entered discovery, with technical workshops under way on its app stack, single sign-on, KYC data and funding integration. The next milestone is a sandbox proof of concept proving the full journey from "Invest" button to first demo trade.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

ACE-17 aims to transform IFRS 17 compliance and financial reporting through an AI-enabled digital platform that combines Microsoft enterprise technologies, Python-based data evaluation, and intelligent analytics. The primary objectives are to automate complex reporting workflows, accelerate actuarial data processing, improve data quality, strengthen reporting consistency, and reduce manual intervention. The platform leverages AI capabilities to enhance data analysis, identify anomalies, support validation, and improve operational efficiency while maintaining appropriate human oversight. Additional objectives include ensuring secure multi-client data management, complete audit traceability, reliable platform availability, and compliance-ready reporting. ACE-17 targets measurable business value through faster reporting cycles, enhanced governance, and a scalable technology foundation for the evolving needs of the insurance industry.

ACE-17 differentiates itself by combining AI-enabled data intelligence, Python-based actuarial data evaluation, and enterprise application ecosystem within a unified IFRS 17 compliance and reporting platform. Rather than treating regulatory reporting as a conventional data-processing exercise, ACE-17 applies intelligent automation to streamline complex workflows, support data validation, identify potential anomalies, and accelerate reporting preparation. Its architecture integrates a Microsoft application and Python processing capabilities to connect data evaluation with secure, client-facing reporting. The platform combines innovation with measurable operational outcomes, delivering a 45–65% reduction in reporting preparation time, 99.9% platform availability, 100% audit traceability, and zero critical security incidents during the reported measurement period. This balance of AI adoption, regulatory reporting, security, and operational reliability makes ACE-17 a distinctive solution.

ACE-17 has delivered measurable improvements in reporting efficiency, operational reliability, and governance. The platform has reduced IFRS 17 reporting preparation time by 45–65%, accelerating reporting cycles and reducing repetitive manual effort. It has achieved 99.9% platform availability, providing dependable access to critical reporting functions, and 100% audit traceability across the defined scope of auditable activities, strengthening accountability and compliance review readiness. Zero critical security incidents have been recorded during the reported measurement period. By combining Microsoft enterprise technologies, Python-based data evaluation, and AI-enabled analytical capabilities, ACE-17 has established a foundation for more efficient, intelligent, and secure insurance reporting while enabling actuarial and financial professionals to focus on higher-value analysis and decision-making.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Replace a fragmented legacy data warehouse (SAP BW) and manual reporting with one cloud data platform that serves as the single source of truth for commercial and logistics analytics of a nationwide supermarket chain. Goals: put the data of Commerce and Logistics in one storage with one dictionary of KPIs, so that business units stop arguing about numbers; shorten the path from source system to report; let business analysts build reports themselves instead of waiting for SAP developers; automate report preparation; cut the time to deliver new analytics; and lay a foundation for the next domains (pricing, procurement, e-commerce, finance, HR) and for ML tools.

The key effect is organizational: the distance between a business user and the data became short. One platform and one data lake gave one dictionary of KPIs and managed data quality. For example, there were several ways to classify a store as like-for-like (LFL); Operations, Commerce and Finance agreed on common criteria that now apply in every report - fewer disputes over figures, faster decisions. In the legacy warehouse only SAP specialists could develop reports; now analysts build them in self-service, the whole Operations domain was delivered this way, and ad hoc analytics is available in SQL and Python. 800 users were onboarded (July 2026) through live meetings, webinars and separate training for top management. 3 years of hot and 10 years of cold history (>10 TB) enable new analytics and create the base for ML. Delivery is hybrid: an in-house team of about 12 for standard domains, an integrator for complex cases, plus an analytics school.

• Data quality: one KPI dictionary with an agreed LFL store definition; daily reconciliation with SAP BW during migration.
• New analytics in ~1 week instead of ~1 month.
• 800 users onboarded (July 2026).
• Self-service instead of SAP-only development: the Operations domain was delivered by business analysts; ad hoc analytics in SQL and Python.
• Data ready daily by ~9:00. 110 datasets, >10 TB, 25 report views, 42 metrics, 50+ dashboards.
• Estimated saving of 1-3 hours per analyst per working day: 6,000-19,000 hours a year across 25 analysts (3-9 FTE, about a quarter of an analyst's day). The estimate is conservative: it excludes the 800 users and data that did not exist before. 

Legacy SAP BW decommissioned on 1 October 2026.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

To enhance Save Mart’s retail operations through the implementation of an automated Lucky Draw Module and the upgrade of the existing Dynamics 365 Finance & Operations system. The project will improve customer engagement, transaction accuracy, operational efficiency, system reliability, reporting, and business continuity across all participating stores.

The project uniquely combines an automated Lucky Draw Module with a Microsoft Dynamics 365 Finance & Operations system upgrade, integrating customer purchase transactions from retail POS/MPOS systems into a centralized and transparent process. It reduces manual intervention, improves transaction accuracy, supports eligibility validation based on defined business rules, and enables reliable winner selection and reporting

Save Mart’s retail operations by introducing a structured and automated approach to Lucky Draw management and enhancing the reliability of the Dynamics 365 Finance & Operations system. The Lucky Draw Module supported centralized customer transaction processing, eligibility verification, winner selection, and reporting, reducing reliance on manual activities and improving data accuracy and transparency. The system upgrade focused on improving system performance, stability, data integrity, and compatibility with existing POS/MPOS operations.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Complete the phased rollout of centralized, passive OT cybersecurity monitoring across five industrial sites by November 2026 without disrupting continuous production. Build a common view of industrial assets, communication flows and anomalies; test SIEM/OT-SOC integration; and establish repeatable deployment and response practices across heterogeneous control systems. The project also includes an R&D stream for ML-based anomaly detection. Planning estimates after full commissioning are approximately 350 visible OT assets, 930 communication relationships and 1,365 traffic flows, extrapolated from the 2021 pilot to five comparable monitoring footprints. These are forecast coverage indicators, not achieved 2026 results.

Industrial cybersecurity monitoring had to be introduced without disrupting continuous metallurgical and mining processes. Active scanning, controller agents and intrusive testing were not suitable as the default deployment approach. The solution therefore observes mirrored industrial traffic passively, as validated in a live production pilot. The rollout must unite different PLC and distributed-control environments under one monitoring model while preserving local operational authority. Its distinctive element is the combination of a safe OT deployment method, centralized multi-site governance and joint work across automation, IT and cybersecurity. A separate research track evaluates ML-based anomaly detection; it is not represented as an already deployed capability.

ACHIEVED BY OCTOBER 2026: a central OT monitoring console was launched, passive sensors entered deployment, and the first network-visibility results were observed. The R&D program and methodology were approved, with its first-stage report recorded as accepted. SIEM/OT-SOC integration is in testing. Full operational commissioning is scheduled for November.

AFTER FIVE-SITE ROLLOUT: >350 visible OT assets, 930 communication relationships and 1,365 monitored flows; 24/7 observation across five sites (43,800 site-monitoring hours annually).

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aimed to transform logistics operations by building a scalable, integrated digital platform covering the complete shipment lifecycle from gateway clearance and first mile through middle mile and last-mile delivery. Key goals were to improve operational efficiency, reduce transportation costs, increase delivery SLA performance, eliminate fragmented and manual processes, and provide real-time visibility of shipments, vehicles and delivery operations. The initiative also aimed to enable intelligent route optimization, AI-driven decision-making, automated workflows and data-driven management through live operational and executive dashboards. A further objective was to establish a future-ready technology foundation capable of supporting IoT, advanced analytics and AI, while enabling the business to scale shipment volumes efficiently across its growing logistics network.

The uniqueness of the project lies in its end-to-end approach to logistics transformation. Rather than implementing separate systems for individual transportation stages, the initiative created an integrated digital ecosystem covering gateway clearance, first mile, middle mile and last-mile delivery within a unified platform. The solution combined real-time vehicle and shipment tracking, route optimization, AI-assisted decision-making, automated workflows, live operational dashboards and management analytics. It was developed specifically around the company's logistics operations and continuously evolved to address real-world operational challenges. The platform also created a foundation for IoT, advanced analytics and future AI capabilities. Its ability to combine operational execution, real-time visibility, intelligent decision-making and scalable architecture in one ecosystem makes it a distinctive logistics technology transformation.

The project delivered significant operational and business improvements by transforming logistics execution into an integrated, data-driven and technology-enabled operation. The platform now supports 30+ hubs and warehouses and manages approximately 80,000 shipments per day across the complete shipment lifecycle. Route optimization and intelligent planning contributed to a 10% reduction in transportation costs, while improved visibility and proactive exception management increased delivery SLA performance by approximately 15–25%. Automation and AI-driven capabilities reduced manual effort by around 45%, improving productivity and scalability. Real-time GPS vehicle tracking and live dashboards provided operations and management with greater visibility and faster decision-making. The platform also established a scalable foundation for AI, IoT, analytics and further automation, enabling continuous innovation while strengthening service quality, operational control and the company's abili

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Between January and December 2026 (first phase of a 2026-2028 roadmap), automate with Artificial Intelligence at least 12 recurring, low-value operating processes across Finance, Treasury, Accounts Payable, Sales/Marketing and Learning & Development, freeing the equivalent of 450+ person-hours per month currently spent on manual work - without growing the 7-person IT team or investing in physical infrastructure (0% CAPEX, 100% OPEX) - so operating capacity can scale with business growth, including expansion into two additional countries, without a proportional increase in organizational headcount.

What makes this project distinctive is its posture: a lean, seven-person IT function used AI not to add one more tool, but to redesign how a mid-sized, multi-country real estate developer operates. Rather than starting with technology, the program starts from one constraint - the organization must grow its business volume without growing headcount in the same proportion - and treats every recurring, low-value task as a candidate for an AI agent or automated workflow. It combines five otherwise separate disciplines (AI adoption, autonomous operations, data, cybersecurity/governance and commercial growth) into one governed portfolio with a single funding logic: fully cloud-based, zero capital investment, 100% operating expense. Equally notable is what it avoided: no "AI theater." Every initiative ties to a measurable operating indicator, and the riskiest part of the plan, per leadership, is adoption, not technology - so change management was funded as a core pillar, not an afterthought

As of September 2026, the first phase is already producing measurable results. Trust/loan disbursement packages for the bank now take under 5 minutes to assemble, down from roughly 30 minutes of fully manual work. The real-time inventory agent has recovered an estimated 840 hours per year of manual reporting capacity across all active developments. The commercial AI agent now delivers a first response to a new sales lead in under 5 minutes, compared to a process that previously depended entirely on staff availability. The new semantic data layer already supports roughly 90% of executive reports without an intermediate spreadsheet, up from about 20% before the project. The AI learning academy has been operating since June 2026, and cybersecurity awareness campaigns are sustaining a phishing-simulation pass rate above 95%. Purchase-order processing, launched in August 2026, is cutting per-document handling time from about 2 minutes to under 10 seconds. Beyond individual metrics.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Turn a twice-yearly physician prescription panel from paper into a self-service digital process, and speed up drug reference consolidation after each data collection wave while keeping the quality of the dataset behind the reporting provided to pharmaceutical companies.

Specific goals:

1. Let physicians record appointments and prescriptions online at the point of care, including new drugs and brands missing from the reference.

2. Keep one golden drug reference while thousands of contributors keep extending it.

3. Replace manual post-production drug reference consolidation with an AI-assisted master data workflow run by one data manager, and substantially reduce consolidation time.

4. Make every change to production data reversible, gated and fully journaled.

5. Give medical experts a structured quality review of every submitted diary before data leaves the platform.

One end-to-end chain replaced paper: a web portal where physicians fill complex cascading drug forms at the point of care, expert quality review, AI-assisted consolidation, and publication to the client's analytics.

The hard part: the drug reference is crowdsourced. 1,700+ physicians extend it while they work, and every wave brings thousands of new spellings of the same drug. That flow of market signals is the value of the panel. We kept it open and kept the reference clean.

Consolidation runs in a sandbox. Production changes in one step behind a blocking integrity gate: if a single link would point at a merged record, the whole batch rolls back. Merged records are kept, not deleted, so any publication is reversible. Physicians never stop working.

AI is grounded: it proposes synonyms, the system finds real golden records, and AI may only choose among them. The data manager makes every decision.

• Live end-to-end platform: paper replaced by one chain of digital entry, expert review, consolidation and publication.

• Scale per wave: 1,700+ physicians, about 80,000 patient visits, about 190,000 prescriptions.

• A multi-level drug reference graph with tens of thousands of entries kept as one golden reference while physicians extend it.

• Millions of snapshot rows processed in the sandbox over dozens of consolidation runs; every production change journaled and reversible.

• 100% of published merges pass a blocking integrity gate: no dangling references in production.

• Every physician entry kept in raw form: no data lost or corrupted while the model evolved.

• 250,000+ expert verdict transitions across multiple review levels.

• Drug reference consolidation time after each wave substantially reduced; run by one data manager.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The Fakeeh Care Group Patient App aims to transform the patient experience by establishing a unified digital front door to healthcare services across FCG facilities. The project seeks to empower patients to actively manage their healthcare journey through convenient, secure, and personalized digital access.

Key objectives include improving access to care, simplifying appointment scheduling and management, enabling access to medical information and results, facilitating communication with healthcare providers, and supporting continuity of care across facilities.

The initiative also aims to reduce administrative friction, enhance operational efficiency, increase patient engagement and satisfaction, and establish a scalable foundation for preventive care, virtual healthcare, and population health management, aligned with FCG’s digital transformation strategy

The FCG Patient App is designed as more than a conventional hospital mobile application. It represents a strategic shift from facility-centered healthcare toward a connected, patient-centered digital ecosystem.

Its distinguishing vision is to provide patients with a consistent digital experience across multiple healthcare facilities and services, integrating clinical information, administrative workflows, and patient engagement within a unified platform.

The application supports FCG’s broader transformation toward proactive, preventive, and value-based healthcare. Its architecture is intended to enable future capabilities such as AI-powered patient assistance, personalized health recommendations, virtual care, wellness services, and remote patient engagement.

This approach positions the application as a strategic enabler of continuous patient relationships rather than simply a transactional appointment-booking tool.

The FCG Patient App establishes a unified digital engagement channel designed to improve patient access, convenience, and continuity of care across the Group.

Key outcomes and intended benefits include:

• Patient experience: Simplified digital access to healthcare services and greater patient autonomy in managing care.

• Operational efficiency: Opportunities to reduce manual administrative interactions and streamline appointment-related workflows.

• Care coordination: Improved connectivity between patients and healthcare services across the care journey.

• Digital adoption: A scalable platform for increasing patient engagement and utilization of digital healthcare services.

• Strategic enablement: A foundation for future virtual care, preventive health, wellness, and AI-enabled patient engagement.

Quantified achievements will be reported using verified adoption, utilization, patient satisfaction, and operational performance indicators.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Our main objective was to take the friction out of pharmaceutical regulatory filings by building a dependable, AI-powered compliance system that handles the heavy lifting of CTD dossier assembly:

• Smarter Drafting: Use Retrieval-Augmented Generation (RAG) and structured templates to generate narrative sections (SPC, RMS, PSUR) grounded strictly in verified source data.

• Automated CTD Splitting: Automatically break down massive master files into clean, organized sections for non-clinical and clinical reports (Modules 4 & 5).

• Reliable Literature Verification: Check in-text citations across PubMed, Crossref, and Google Scholar simultaneously, using an LLM to lock down accurate, audit-ready references.

• Audit-Proof Traceability: Track the origin of every single paragraph with confidence scores to satisfy strict regulatory inspections.

• Real-World Impact: Shrink filing timelines from five to six months down to two to three weeks, removing costly human errors along the way.

What sets this project apart is that we didn't just throw a generic chatbot at compliance paperwork, we built an engineering system where hallucinations are strictly controlled and every word is auditable:

• Hybrid Architecture: We combined Retrieval-Augmented Generation (RAG) for drafting complex narratives (SPC/RMS) with deterministic regex parsing to neatly slice and organize hundreds of pages of non-clinical and clinical reports into CTD folders.

• Three-Way Citation Engine: Instead of manual literature searches, our system queries PubMed, Crossref, and Google Scholar in parallel. It resolves medical synonyms on the fly and uses an LLM validator to hit a verified 92% match rate.

• Inspection-Ready Provenance: Every single generated sentence links back to its exact source chunk, similarity score, and confidence level, giving regulatory auditors complete transparency.

• Bridge to Industry: A rare model where applied academic research was deployed directly into commercial enterprise production.

Rolling out this platform completely changed how our regulatory team works day to day. The most immediate win was time: preparing an entire registration dossier used to tie up senior specialists for five to six months, but we brought that down to just two to three weeks. That alone helped us get products to target international markets months ahead of schedule.

The citation engine solved one of our biggest administrative headaches by hitting a 92% automated match rate across PubMed, Crossref, and Google Scholar, saving countless hours of manual literature checks. Core documents like the 12-section SPC now come together in about seven and a half minutes instead of days of drafting. Most importantly, we didn't sacrifice compliance for speed. Every generated passage carries full source attribution and a confidence score, giving our teams the audit-ready transparency they need to submit with total confidence

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The primary goal of SweetSync was to transform Faran Sugar Mills from a legacy technology environment with manual, paper-based processes into an integrated, intelligent, and digitally enabled enterprise.

The project encompassed end-to-end digital transformation across multiple business functions, including Cane Management, Sugar Production, Supply Chain, Inventory, Finance, Sales, HR, Electronic Loading, and other critical operational areas. It aimed to automate workflows across 15 departments (160 workstations), to enhance cross-functional integration, and reduce dependence on manual documentation.

A key innovation was the application of AI-driven analysis using cane testing records and production-related data to support operational insights and informed decision-making. A customized Business Intelligence (BI) solution further empowered management with consolidated business insights, while the integration of the government-mandated FBR tracking system enabled digital invoicing.

SweetSync turns traditionally manual sugar mill operations into a connected digital value chain, spanning cane receipt, production, supply chain, inventory, finance, sales and invoicing across 15 departments and 160 workstations.

What makes it distinctive:

1. AI-driven insights: AI-based analysis of cane testing records and production data highlights cane quality variations and production trends, supporting better-informed operational decisions.

2. Compliance embedded in operations: integration of the government-mandated FBR tracking system with in-house systems enables digital invoicing within normal workflows.

3. In-house capability: a technology partner and the internal IT team built business-focused solutions, including an attendance portal, strengthening internal technology skills.

4. Management intelligence: a customized BI solution consolidates information into actionable insights, replacing scattered paper reports.

SweetSync transformed a sugar mill’s paper-based operations into an integrated digital ecosystem across 15 departments and 160 workstations, delivering measurable results:

• 90% reduction in management reporting time, enabling faster access to business insights.

• 75% reduction in paper-based forms, advancing paperless workflows. • 85% reduction in loading turnaround time through electronic loading.

Digitized cane management, supply chain and inventory processes improved operational visibility and control. Customized Business Intelligence (BI) enabled timely, data-driven decisions, while FBR tracking integration and digital invoicing strengthened regulatory alignment. An internally developed attendance portal enhanced in-house IT capabilities and supported sustainable innovation.

SweetSync has advanced operational efficiency, management visibility and digital maturity, establishing a strong foundation for continued digital transformation in Pakistan’s sugar industry

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aims to create a unified system for operational accounting and management of cattle production across several farms and to transition the processes of several livestock complexes to centralized digital management.

The project’s objectives are: daily planning, assignment, and monitoring of veterinary, zootechnical, and production activities for dairy and beef herds numbering more than 10,000 head; generating detailed analytics for operational management decisions; unifying business processes and aligning farm‑level accounting with the enterprise’s regulated accounting; complying with the requirements of the legislation of the Republic of Belarus, including animal identification and traceability.

The target state is the industrial operation of a system in which livestock movement, treatment, milk quality, shipment, and product sales are recorded according to uniform rules and monitored at the enterprise level.

The uniqueness of the project lies in the localization of the Russian industry‑specific solution “1C: Digital Livestock Farming” in accordance with the legislation of the Republic of Belarus and for the accounting of enterprises within the system of the Administration of the President of the Republic of Belarus.

The enterprise has developed its own documents and printed forms. Activities involving animals from different areas of the farm are documented in a single document; when shipping to meat processing plants, the rejected part of the carcass is taken into account; treatment records are entered according to a scheme and schedule; veterinary documents are linked to zootechnical documents.

The solution was selected through a tender, has compatibility confirmation, and is included in the registers. The basic functionality works without an annual subscription fee; new costs arise when expanding licenses for the livestock or when developing forms and reports.

The project was completed on time and put into commercial operation. The enterprises maintain operational accounting of cattle within a single system linked to the agricultural enterprise’s accounting department and to the AITS traceability system.

Identification accounting of the livestock, regulated printed forms, calculation based on the value‑added tax rates of the Republic of Belarus, as well as monitoring of treatment, milk quality, movements, shipments, and sales are provided. Management has access to monitoring of the herd structure, reproduction, culling, and milk quality by farm. The shipment to meat processing reflects the rejected part of the carcass; the sale of livestock products is carried out in accordance with contracts with counterparties.

The staff has been trained during joint trial operation. The first line of technical support is provided by the customer’s specialists. The system is used as a working tool for daily production management.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The goal of the project is to develop, test, and implement the AgroScope hardware and software system — an intelligent decision support system for agronomic practices. The project is aimed at creating an integrated drone-and-satellite system based on artificial intelligence that provides monitoring of the state of agricultural land, analysis of crop conditions, and generation of recommendations for agronomists. The key objective is to increase crop yields and the efficiency of crop production through timely and accurate analytics, as well as to reduce fertilizer and herbicide costs by 10–15% and lessen the environmental impact.

The uniqueness of the project lies in the creation of an integrated ecosystem that combines satellite and drone monitoring with advanced machine learning methods and geoinformation technologies. Unlike fragmented solutions, AgriSoft automates the full cycle: from identifying areas of interest and planning UAV flight routes to image segmentation, crop classification, and data visualization. A distinctive feature of the project is its comprehensive approach, which includes not only applied automation tasks but also supporting functions (data lifecycle management, ML pipelines, infrastructure administration), ensuring the system's development and ongoing model retraining from year to year.

Achieved Results:

• Successfully integrated 219 field boundaries covering a total area of 21,324.2 hectares without errors.
• Introduced digital agricultural monitoring using unmanned aerial vehicles (UAVs) and artificial intelligence algorithms for the first time.
• Automated aerial image processing, detection of problematic areas, and generation of analytical maps.
• Established a foundation for targeted field inspections and variable-rate application of agrochemicals.

Estimated Economic Impact: Up to KZT 28.18 million in annual savings across 18,787 hectares. Expected reductions in herbicide costs range from 9% to 15%, while fertilizer costs are projected to decrease by 7% to 14%.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The Nanyang Technological University (NTU) Student Activities Centre (SAC) offers flexible spaces for both quiet study and group meetings. Additionally, the One Stop@SAC lounge was recently transformed to centralize scattered student services into a single, integrated physical and digital hub.

Key objectives:

• Unified Hub: Consolidate academic matters, finance, housing, admissions, campus life, and IT services at the One Stop@SAC, replacing traditional queues with a personalized, name-based QR system.

• Accelerate Financial Aid: Integrate HOMES (Singapore National Database) to cut manual validation by 60% and reduce processing to under 2 minutes.

• Scale Omnichannel AI: Deploy a 24/7 multilingual AI-IVR and ServiceNow GenAI triage to absorb routine IT and administrative volume.

• Elevate Experience: Maintain >90% CSAT, achieving 4.9-star Google Reviews and 92% Financial Aid satisfaction, fundamentally shifting support from reactive to proactive.

This initiative uniquely merges national data infrastructure and enterprise AI to revitalize the in-person campus experience. Guided by the principle, "Technology handles the volume; humans handle the value", it harmonizes high-tech speed with high-touch care.

Integration with the national HOMES system slashed financial aid means-testing by >90%, enabling application processing in minutes.

Concurrently, issues raised via the student portal undergo GenAI triage (>50% faster resolution), while a 24/7 multilingual AI-IVR resolves 75% of helpline calls autonomously to absorb routine administrative volume.

At the physical Tech Lounge, engineers use the LLM KOPI platform to instantly troubleshoot complex issues without reinventing fixes. By replacing anonymous ticket numbers with a personalized, name-based QR queue, liberated staff act as empathetic counselors and consultative advisors, securing a 4.9-star rating and eliminating historical service gaps.

Operational Efficiency & Velocity:

• Financial Aid Acceleration: Integrating with the national HOMES database eliminated 60% of manual verification labor. Application processing time plummeted by >90% (dropping from 55 minutes to <2 minutes).

• ServiceDesk GenAI Triage: Achieved >90% categorization accuracy & reduced overall incident resolution times by >50%.

• Voice Automation: 24/7 multilingual AI-IVR successfully resolves 75% of routine inquiries across 8 core service areas autonomously.

Customer Experience & Workforce Impact:

• Exceptional Satisfaction: Sustained >90% overall CSAT score. Dedicated Financial Aid surveys registered a remarkable 92% satisfaction rate.

• Reputation Turnaround: Walk-in Google Review ratings surged from baseline 3.3 stars to exceptional 4.9 stars.

• Staff Elevation: Liberated from transactional data processing, frontline personnel successfully transitioned into empathetic counselors and consultative advisors.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aims to achieve 100% digital and paperless management of the MBBS student lifecycle for 150/250-seat batches through ERP and mobile applications. Admissions, fees, attendance, timetable, assignments, assessments, certificates, hostel and clinical activities are managed digitally. Biometric attendance and mobile access provide real-time academic visibility. Digital certificate processing reduces manual effort and turnaround time. ERP-based clinical tracking and digital logbooks ensure complete traceability of student academic activities. QR-based hostel movement and automated OTP/WhatsApp alerts enable 100% digital monitoring of student entry and exit and timely parent communication. The implementation reduces paperwork, manual dependency and data duplication while improving transparency, accountability, operational efficiency and student services.

The uniqueness of the project lies in its end-to-end digitalisation of the MBBS student lifecycle, going far beyond the commonly implemented modules such as timetable and attendance. The project integrates academics, assessments, certificates, clinical postings, digital logbooks, hostel management, student movement, parent communication and administrative services on a single ERP–mobile platform. It connects student activities from admission to clinical training and hostel operations, creating a unified, paperless and traceable ecosystem. This level of integration across multiple academic, clinical, administrative and residential processes makes the project distinctive among medical colleges.

The project provides real-time, dashboard-based visibility of the complete student and faculty journey. Management can monitor student performance, attendance, academic progress and overall engagement through a central dashboard. Coordinators and faculty have role-based dashboards to track student performance, including session-wise attendance, assignments, topics covered, content delivered and academic activities. Faculty performance can also be monitored through measurable parameters such as sessions conducted, content completion and published academic articles. Parents have access to a dedicated mobile application to track their child’s attendance, academic performance and overall progress. The integrated dashboards have improved transparency, accountability, timely monitoring and data-driven decision-making, enabling management, faculty and parents to identify gaps and take timely corrective action.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aims to transform commercial operations and establish a unified digital sales ecosystem across the media group’s six primary business verticals (SRMG Think, Academy, Labs, SRMGx, Studios, and SMS). By implementing Salesforce Media Cloud, the initiative replaces fragmented lead handling and disjointed workflows with an end-to-end "Lead-to-Cash" platform tailored to diverse revenue models, including advertising, media planning, sponsorships, research advisory, media production, and training. 

Key objectives include establishing 360-degree client visibility, centralizing lead management to avoid cross-vertical contact overlap, streamlining commercial/financial approvals and NDA workflows, and enhancing cross-functional collaboration. The platform optimizes sales pipelines, delivers real-time executive dashboards for revenue target tracking, and provides a scalable cloud foundation for future business growth.

The first Salesforce Media Cloud implementation in the Middle East earned the Salesforce Partner Innovation Award (Media & Entertainment) and "Go Live" Award for modernizing sales, customer engagement and operational agility. It unifies research advisory, experiential events, film production, media academies and publishing in one Lead-to-Cash process, combining dynamic conditional logic, MuleSoft integrations and autonomous Agentforce AI. By automating repetitive analytical tasks, it enables teams to focus on creative innovation and human storytelling. The platform connects government tenders through Etimad, direct awards, media planning across 30+ titles reaching 165M viewers, letter of guarantee tracking and multi-region e-invoicing interfaces covering ZATCA, FTA and HMRC. Its distinction lies in bringing diverse commercial models and complex regional requirements into a single digital ecosystem, combining AI-enabled automation with the flexibility needed across all media businesses

The Salesforce Media Cloud implementation successfully transformed SRMG’s media commercial operations by establishing a unified platform across multiple business entities and media offerings. It standardized the end-to-end sales journey from lead and opportunity management through media planning, ordering, fulfilment and delivery. The project created stronger commercial governance, improved pipeline and revenue visibility, and greater control over complex media sales processes. Most importantly, it provides SRMG’s media businesses with a scalable and consistent commercial foundation, enabling teams to operate more efficiently, make better-informed decisions and support future business growth.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Create a unified, automated newsroom platform that serves as the digital backbone of content operations, connecting people, processes and technology to drive higher productivity, faster time-to-publish, improved governance and scalable growth without increasing workforce costs. Entire workflow is automized with notifications.

Our project NewsOrbit_360 is an unique initiative because it goes beyond traditional newsroom digitization by creating a single, intelligent operating platform that unifies people, processes, content and technology across the entire newsroom ecosystem.

Unlike conventional newsroom systems that automate isolated workflows, this platform delivers end-to-end orchestration of newsroom operations, from content planning and assignment to production, publishing, monitoring and analytics. It eliminates fragmented tools, manual handoffs and duplicated effort by creating a seamless digital workflow.

NewsOrbit_360 delivered significant operational and business benefits by transforming fragmented newsroom processes into a unified, automated workflow ecosystem. The platform substantially reduced content turnaround times by streamlining collaboration between reporters, editors, graphics teams, video editors, producers and telecast operations. Automation of content collection, clipping, approvals and workflow management increased overall productivity and enabled teams to handle higher content volumes without additional manpower.

The solution strengthened governance through centralized approvals, comprehensive audit trails and end-to-end process visibility, ensuring greater accountability, compliance and traceability across newsroom operations. Real-time analytics and performance dashboards empowered leadership with actionable insights for data-driven decision-making and resource optimization.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The goal of the project was to move TEMPO's fraud and cost control from manual, reactive reviews to a predictive, data-driven model. OCTO was designed to use Machine Learning to detect anomalies, cost distortions, and potential fraud across assistance service requests, and to direct analysts to the cases that matter most.

The project aimed to reduce financial losses, cut manual review effort, speed up investigations, and give the company the ability to scale its operations without losing control over costs and margins.

OCTO stands out by applying Machine Learning to a highly specific operational challenge: identifying anomalies, cost distortions, and potential fraud within assistance services. Rather than relying only on static rules or manual reviews, OCTO learns from historical patterns and highlights atypical behaviors that may indicate financial or operational risk.

Its uniqueness also comes from combining fraud prevention, cost intelligence, and operational efficiency in the same solution. OCTO does not replace human judgment; it makes it more effective by directing analysts to the cases that deserve attention most. This allows TEMPO to act earlier, scale controls, and protect margins with a more intelligent and data-driven approach.

OCTO delivered measurable financial and operational impact:

• Approximately BRL 3 million in annual cost avoidance, thanks to earlier and more accurate detection of anomalies, cost distortions, and potential fraud.
• Around 25% reduction in fraud-analysis headcount, as ML-based prioritization replaced broad manual reviews.
• Faster, more focused investigations: analysts now work on a prioritized list of suspicious cases instead of reviewing requests at random.
• Stronger cost control and scalability: the company can grow its volume of service requests while keeping controls consistent.

Overall, TEMPO shifted to a proactive approach to fraud prevention, with better decisions, protected margins, and a solid foundation for further use of AI in operations.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aimed to establish a unified enterprise ERP platform through the global implementation of Microsoft Dynamics 365 Finance & Operations across 46+ legal entities, supporting more than 2,000 employees. The implementation standardized core enterprise functions, including Finance, Supply Chain Project Accounting, and operations while accommodating fully customized specialized business processes such as Subscriptions, Printing & Distribution, Advertising, Freelancer Management and Request of Payment (RoP).

The project sought to improve cross-functional process consistency, strengthen operational control, consolidate business data, and enhance reporting and management visibility across geographically distributed operations. By combining standard ERP capabilities with tailored business functionality, the completed implementation established a scalable enterprise foundation aligned with the organization's diverse operational requirements

The project is distinguished by creating one global ERP backbone that combines enterprise standardisation with the specialised operating requirements of a diversified media organisation. Microsoft Dynamics 365 Finance & Operations was implemented across 46+ legal entities and 2,000+ employees, replacing fragmented legacy and isolated solutions with a common platform. Beyond standard Finance, Supply Chain and Project Accounting, the solution incorporates tailored capabilities for Advertising, Subscriptions, Print & Distribution, Freelancer Management and Request of Payment (RoP). These processes are integrated directly with financial controls, reporting and payment workflows rather than operating through disconnected applications. This combination of global scale, media-specific functionality, workflow automation and consolidated visibility makes the implementation significantly broader than a conventional ERP deployment.

The successful implementation of Microsoft Dynamics 365 Finance & Operations transformed SRMG from legacy and fragmented systems into a unified, Group-wide ERP platform serving 46+ legal entities globally. The program standardized finance, procurement and operational processes across multiple geographies and currencies, strengthening governance, control and enterprise-wide visibility. It significantly reduced manual and repetitive activities through process automation while enabling consolidated financial reporting and more timely, data-driven decision-making. The project established a scalable digital foundation that supports SRMG’s global operating model and future business growth.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

1. Create a single, objective competency assessment system for IT, Digital, Data and CISO employees.

2. Develop a unique competency matrix for each specialization, benchmarked against the market and tailored to the bank’s specifics.

3. Implement a three-way assessment based on a single matrix: self-assessment, AI-generated test and manager assessment.

4. Build an internal talent marketplace based on common criteria.

5. Gain visibility into every specialist’s actual skills and quickly assemble and reassemble teams around business needs.

6. Apply the same matrices in recruitment to compare external candidates directly with internal talent.

7. Identify skill gaps and strong competencies, find internal experts to act as trainers, and build personalized learning based on competency levels.

Skill-Based Culture is Halyk’s approach to talent management that puts skills, rather than job titles, at its center. The approach brings together three independent views of the same competencies: the employee’s self-assessment, a knowledge test created with a state-of-the-art AI model, and the manager’s assessment — all three are conducted against a single competency matrix designed for the specific specialization. Managers and experts are involved at every stage, from building the matrices to reviewing test questions, so the quality and relevance of the assessment remain under human control. As a result, the Bank gets a structured picture of skill proficiency levels and competency gaps, while each employee receives personalized AI recommendations immediately after completing the assessment. The next phase is personalized learning paths from basic to advanced level, built around the competencies of each specialization.

More than 1,000 employees in IT, Data, Digital and CISO were assessed between December 2025 and June 2026. Coverage is about 50% of Head Office headcount, excluding the contact center. • More than 170 specializations and more than 1,000 competencies have been defined. A bank of 250 questions has been created for each specialization (around 40,000 questions in total); the test lasts 90 minutes and every test is unique. • The assessment system makes it possible to evaluate whether an employee matches their current grade, identify skill gaps, and identify employees whose results exceed their current level.

Every employee receives personalized AI recommendations immediately after the assessment; the first learning paths and HR analytics are already live, and the full personalized learning module launches in November 2026. • The figures above reflect implementation and coverage results. The impact on business metrics, retention and productivity has not yet been quantified.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aims to digitalize and improve production management at an agricultural machinery manufacturing plant through the implementation and continuous enhancement of a Manufacturing Execution System (MES). Its objectives include real-time monitoring of equipment status and downtime, improved production planning, traceability of parts throughout manufacturing workshops, and better visibility of production progress for management. The project also aims to standardize technological routing and operation data, improve workforce timekeeping and overtime calculation, and ensure consistent transfer of relevant personnel and attendance data to the 1C system. These improvements support greater transparency, data accuracy, and operational control across manufacturing processes.

The project integrates several interconnected aspects of manufacturing operations into a unified MES environment. Equipment status and downtime are tracked using production data and machine-button events, while workshop production plans provide visibility into equipment conditions and work progress. A dedicated parts-traceability function enables management to follow each part through successive workshops, including quantities produced, accepted by technical quality control, and awaiting inspection. Technological routing, operation standards, and production schedules are linked to support more consistent planning. The system also aligns daily overtime calculations with personnel orders and maintains consistency between timesheets, employee records, and data transferred to 1C. The solution continues to operate with its interface and controls available during internet connectivity interruptions.

In October 2026, 359 new machines were added to the mechanical workshop records, and more than 1,700 machine-button events were registered. The parts-traceability function recorded 739 batches of parts across workshops, with 180 transfers of parts to the warehouse. The personnel module processed 157 payment orders and 15 transfers, while 7 employee departures were registered. Turnstile passages exceeded 113,000. Technologists entered more than 1,000 new operations and more than 1,000 technological transitions; over 2,000 parts and 1,800 materials were linked to operations. The system improved visibility of equipment status, production progress, parts movement, and consistency of timekeeping data.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

To develop and integrate an Order Confirmation Form workflow within the existing Salesforce Sales process, triggered when an Opportunity is marked as Won. The workflow enables the sales team to generate order confirmations directly within Salesforce, communicating precise product specifications, dimensions, spare requirements, target delivery dates, applicable taxes, and freight charges based on delivery location and transportation mode. It provides the production team with accurate, transparent, and timely order information for effective production planning and delivery execution, eliminating the need for sales personnel to switch to another platform to generate order confirmations.

The key uniqueness of the project lies in integrating order confirmation generation directly into the existing Salesforce Opportunity workflow, eliminating the need for an external application. It bridges the gap between sales and production by capturing detailed product specifications, dimensions, spare requirements, target delivery dates, tax details, and location- and transportation-based freight charges in a standardized format. The workflow enhances transparency, minimizes manual communication and errors, and enables seamless coordination between departments. Additionally, it maintains centralized, company-wise historical order data within Salesforce, ensuring easy retrieval, traceability, and reference for future orders, production planning, and business analysis.

The project streamlined order confirmation by integrating the process into the existing Salesforce Opportunity workflow. Upon winning an order, the Sales team can generate the confirmation form directly within Salesforce without using an external platform. It captures product specifications, dimensions, spare requirements, target delivery dates, applicable taxes, and freight charges based on delivery location and transportation mode. This ensures accurate and timely communication of customer requirements to Production, enabling better production planning and delivery coordination. The standardized process improves transparency, reduces manual communication, and minimizes errors. Centralized, company-wise historical order records enable easy retrieval, traceability, and reference for repeat orders and customer queries. By leveraging the existing Salesforce platform, the solution improves operational efficiency, data consistency, and collaboration between Sales and Production

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Turn B2B lead qualification at one of Brazil's largest logistics and e-commerce delivery companies from a manual, rep-dependent process into an AI-driven, always-on digital operation. Specific goals: (1) shorten the lead qualification cycle, which averaged 38 days; (2) reduce the cost of qualifying each lead; (3) standardize qualification through an objective, automated Lead Score; (4) eliminate manual CRM updates and keep a complete, traceable history of every interaction; (5) give B2B prospects an immediate 24/7 response on the channel they already use, WhatsApp; and (6) let account executives focus only on sales-qualified opportunities, so the commercial pipeline can scale without proportional headcount growth.

This is not a chatbot or a scripted funnel. The AI works as an autonomous pre-sales agent that does a human SDR's job end to end. It opens the conversation on WhatsApp, understands free-text questions, answers from a corporate knowledge base, handles objections and runs the qualification interview. In the same conversation it validates the prospect against official business registries (tax ID, registration status, segment, address, company size), computes a Lead Score and decides on its own whether the lead stays in nurturing or becomes an SQL. It then books the meeting in the account executive's calendar and writes everything back to the CRM. People step in only on hand-off. Result: qualification cycle cut from 38 days to about one week, cost per qualified lead down ~80% (4.9x cheaper), and same-day proposals for engaged leads.

Results. Qualification cycle cut from 38 days to about one week (-80%), with same-day proposals for engaged leads. Cost per qualification down from R$ 56.86 to R$ 11.57 (-80%, 4.9x cheaper). 24/7 availability, standardized qualification, automatic CRM updates with full traceability, and a sales team focused on qualified opportunities.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

We built Velopy with a vision of an enterprise transformation platform where IT and business units manage services, projects and actions through a shared way of working. Our goal was a lean, flexible structure that delivers visibility, collaboration and data integrity across the organisation without forcing every team into the same way of working. The need came from shared work being tracked in separate systems, project methods varying from team to team, and the lack of a single, holistic data source to support decisions. We designed one platform, aligned with Agile and ITIL principles, that manages services, projects and all actions end to end. We aimed to make every project step, effort spent and budget visible, and to produce clean, reliable data from a single source. Through dynamic workflow design, we set out to let every team adapt the platform to its own needs, to preserve and reuse company know-how in the platform, and to integrate openly with other enterprise systems.

Velopy’s uniqueness lies in bringing corporate standardisation and team autonomy together on one platform. Service, project, change and action management are unified in a single data model, while every team designs its own record types, fields, statuses and transitions without code. The organisation gets one common governance and data standard, and teams are never forced into one-size-fits-all processes. Velopy does not just record work; it turns accumulated know-how into decision support. Bridge interprets cross-department Gantt plans, identifies delays and dependencies, and suggests actions. Incident analytics draws on past resolutions to suggest solutions for new records. Company know-how no longer stays with individuals; it builds up in the platform as a reusable asset. The platform was built in months by a six-person in-house team using AI-assisted development. With open integration, multi-company use and a scalable architecture, it can be adapted to other organisations.

Velopy has been used by all CDO teams since July 2026. It now serves 262 active users across 19 workspaces in 7 departments, with more than 6,000 work items created and more than 35,000 operations performed. Work that departments previously tracked in their own separate systems now sits in a single data source. Services, projects and actions follow one standard method, and every step, effort and budget is visible to management on one screen. Teams design their own workflows without needing development effort, while company know-how builds up in the platform and turns into solution suggestions. Moving away from licence-based tools saves USD 100,000 in annual licence costs. The platform has been presented to the 16-company Sabancı Group as a scalable product.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The main goal of the project was to establish a unified digital ecosystem for IT service management at the Center for Information Technologies (CIT), improving service quality, operational efficiency, and transparency.

Key objectives:

• Centralize IT support requests from multiple communication channels in a single system.

• Automate request classification, routing, and SLA monitoring to reduce resolution times and prevent lost requests.

• Provide subordinate organizations with a self-service portal for submitting and tracking requests.

• Improve management visibility into IT operations, staff workload, and service performance.

• Streamline project management, including resource allocation, budgeting, and timeline control.

• Digitalize electronic document workflows and integrate them with government information systems.

• Reduce implementation and maintenance costs through a flexible low-code platform.

The project replaces reactive support with a platform-based service management model built on low-code. Requests from email, phone and messengers land in a single digital hub, where the system classifies and routes them automatically, tracks SLA deadlines and feeds management dashboards. All of it is configured visually.

The solution fits a heterogeneous public-sector infrastructure: LDAP/Active Directory and email integrations were set up with platform tools, with no changes to the core. Two scenarios required pro-code (TypeScript): integration with the interdepartmental electronic document exchange system and customization of the “External User” module. Low-code covered most of the work; code was used only where needed.

Because the setup is configuration rather than development, it can be replicated in other organizations: the same hub extends to project management and interdepartmental document workflow without rebuilding what already exists.

Request processing time was reduced by 40%: average incident resolution dropped from several days to 3–5 hours. SLA compliance reached 95% thanks to automatic reminders and priority control.

All requests, including those from subordinate organizations, now pass through a single system with visible status, owner, change history and deadlines (100% transparency), so no request is lost. Management gained analytics on staff workload, request types and bottlenecks for resource allocation, and the External Portal connected subordinate organizations to the unified contour.

Low-code instead of hard-code development reduced implementation costs by 50% and development costs by 60%; time to full production fell from 9 to 5 months.

The customer can adapt processes to new requirements without external developers. The ecosystem already includes the “External User” solution and ELMA365 Projects, with electronic document management integrated into Belarus’s interdepartmental system.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Chint Solar Europe grew from a German headquarters into a business with teams in eight European countries, but IT support was still built around the German working day. Our goals were to:

• Extend support from German business hours to cover colleagues across three time zones, from sunrise in Romania to sunset in Portugal and the UK

• Reduce the total cost of IT support by replacing per-ticket, on-demand billing with a predictable framework model

• Move from ad hoc support to ITIL-based service management with SLAs, a service catalogue and regular reporting

• Bring Microsoft 365, network security and endpoint management under one accountable managed service

• Free our small internal IT team from daily firefighting to focus on strategy, security and AI enablement

This was not just a provider change, but a redesign of how a young IT function serves a European business. We moved from a support model built around one country's office hours to one that follows our colleagues across time zones, and we did it at a 20% lower cost by replacing per-ticket billing with a framework agreement built on standard ITSM services. With a lean team, we defined our service model and expectations first, then ran a competitive RFP to find the right partner. Governance, security and architecture stay in-house, while the partner delivers day-to-day operations, so accountability stays with the business. We also used AI from the start: our first service performance dashboard was built with Copilot, and service data drives monthly improvement reviews. New users, new offices and new services, including AI tools, now flow through one standard catalogue instead of one-off efforts.

• Better service coverage: support extended from German business hours to all eight countries across three time zones, so every colleague is supported within their own working day

• Around 20% annual cost saving, by moving from on-demand, per-ticket billing to a framework agreement with standard ITSM services

• Optimised processes: one service desk for 150 users, with standardised onboarding, access, software and hardware requests tracked against SLAs

• Transparency for management for the first time, through monthly SLA reporting, service reviews and a Copilot-built service dashboard

• Central endpoint monitoring and software inventory, strengthening our security baseline

• Internal IT capacity freed for strategic work: AI strategy and governance, and the upcoming company-wide security rollout

• Colleague survey and company-wide service dashboard planned for December 2026, after six months of operation

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Give IT leadership of the bank a real-time, verifiable picture of where delivery work is and where it is stuck — without status meetings, manual reports or surveillance.

1. Replace manual status collection across 37 delivery teams with an automatic view built from Jira, GitLab and Slack events.

2. Let every manager see their own team (scoped by the Active Directory management hierarchy) and drill from a person to the exact task, merge request or review behind any status.

3. Link code to business work: connect GitLab activity to Jira issues automatically, so progress on a story is visible without asking developers.

4. Motivate engineers transparently: reward delivered results (closed tasks, merged and reviewed code) with internal BAKAI Coin and an open leaderboard, with anti-fraud rules.

5. Keep trust: make hidden monitoring technically impossible rather than forbidden by policy.

Most activity trackers can say "employee is inactive". This system cannot — by design. There is no "idle", "absent" or "not working" value in the database schema, so such a status can never be shown. Absence of events is displayed as "not enough data", never as a judgment about a person.

Every status on the map is derived from a concrete Jira, GitLab or Slack event and shown with a link to that event, so any conclusion can be verified by the manager and by the employee.

Slack message text is discarded before it reaches the database or logs; only metadata is used.

The office is rendered as an interactive 3D floor (three.js) where teams sit in zones and employees' states update live over WebSocket — readable both on a laptop before a stand-up and on a wall TV in the office.

Gamification pays for results, not activity: no rewards for commit counts, messages or "online time"; one task is paid once per task–employee pair, self-merges without a peer approval earn nothing.

Production data, 15.09–22.10.2026:

• 215 employees, 37 teams, 7 tribes in one live view; 144 users signed in (67% of staff), 70–108 weekly active users.

• 53 Jira boards and 44 projects, 258 GitLab repositories connected; 14,289 Jira issues and 27,540 GitLab events processed, 96,000+ webhooks.

• 58% of merged MRs automatically linked to Jira issues; 12,653 status comments posted to Jira with no manual work.

• 2,949 Jira issues resolved since launch are visible to managers with their code activity.

• BAKAI Coin: 182 engineers rewarded for closed tasks, testing, merges and reviews.

• Anti-fraud flagged 4,457 suspicious accruals (self-merges, self-reviews, too-fast closures) and capped 325.

• Zero storage of message content; no "inactive" status exists in the system.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The primary goal of the FlowCraft project is to develop an integrated automation platform for ERP reporting and data maintenance that reduces manual work, improves data accuracy, and streamlines business operations across ERP systems, including Microsoft Dynamics 365 Finance & Operations.

FlowCraft is unique because it combines ERP report automation, data maintenance, validation, and process optimization within a unified framework. It is designed to reduce repetitive manual tasks, improve data quality, and streamline reporting across multiple ERP modules, including Microsoft Dynamics 365 Finance & Operations.

Key Unique Features

1. Centralized Reporting Automation: Automates the preparation of multiple operational and management reports using standardized formats and business rules.

2. Intelligent Data Maintenance: Streamlines routine ERP data updates, corrections, validation, and duplicate-record identification to improve data consistency.

3. Cross-Module Reporting: Supports consolidated reporting across Finance, Procurement, Inventory, Supply Chain, Sales, Warehousing, and Retail operations.

The FlowCraft project improves ERP reporting efficiency and data maintenance by reducing repetitive manual tasks, standardizing reporting procedures, and strengthening data accuracy across business operations.

1. Improved Reporting Efficiency: Automated report generation reduces the time and effort required to prepare operational and management reports.

2. Enhanced Data Accuracy: Data validation procedures help identify duplicate records, missing information, and inconsistencies, improving the reliability of ERP data.

3. Reduced Manual Workload: Automation of repetitive reporting and data maintenance tasks allows IT teams and business users to focus on higher-value activities.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project was launched to eliminate a critical business risk: the concentration of knowledge about three mission-critical legacy applications in a small number of specialists and external dependencies. As Verzani & Sandrini accelerated its growth, ensuring the continuity, maintainability and governance of these systems became essential. The initiative aimed to recover institutional knowledge, establish application governance, strengthen corporate ownership of source code and deployment processes, and enable internal teams and future partners to operate within a controlled and auditable environment. Through AI-assisted knowledge recovery, the project reconstructed architecture, technical dependencies, business rules and operational procedures while implementing repositories, documentation portals, CI/CD pipelines and approval workflows. The result was a scalable foundation for business continuity, operational autonomy and future modernization.

What makes this project unique is its ability to transform concentrated knowledge into a scalable corporate capability. Rather than delivering documentation as a one-time exercise, the initiative combined AI-assisted reverse engineering, governance, DevOps automation and operational accountability into a sustainable operating model. Knowledge previously held by a few specialists became a corporate asset accessible through repositories, a documentation portal and controlled development processes. By connecting AI-generated knowledge, living documentation and governed software delivery, the project reduced dependency on individuals, strengthened business continuity and created a foundation for future modernization and growth.

The project successfully recovered and structured knowledge from three mission-critical legacy applications, transforming information previously concentrated in a limited number of specialists into a reusable corporate asset. Approximately 5,000 documentation artifacts were generated, covering architecture, technical frameworks, operational procedures, business rules and application functionality, representing around 550,000 documented lines. More than 120 successful pipeline executions validated the new automated build and delivery processes. The initiative established corporate repositories, a centralized documentation portal, CI/CD pipelines and governance controls that separated development, validation and production approval responsibilities. As a result, Verzani & Sandrini strengthened business continuity, reduced dependency on individual knowledge, increased operational autonomy and created a scalable foundation for future application modernization and organizational growth.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aims to transform IT support into an intelligent self-service model available to employees 24/7. AI-Sara provides fast and consistent answers to common IT-related questions in Russian and Kazakh using verified corporate knowledge and historical support data. The key objectives are to reduce repetitive manual consultations, shorten response time, improve user experience, increase reuse of corporate knowledge and scale IT support without proportional staff growth.

AI-Sara is an enterprise AI support system operating fully within the Bank’s secure internal environment.

The solution uses 2,267 verified Q&A items and data from 189,338 closed IT requests. It understands natural-language questions and provides contextual answers in Russian and Kazakh.

Unlike a traditional scripted chatbot, AI-Sara combines generative AI, corporate knowledge, Service Desk expertise, analytics and ITSM processes in one platform.

The model is deployed On-Premise on corporate GPU infrastructure. All data remains inside the Bank, with no external internet requests and no dependency on external AI providers. The project was implemented without additional external license costs and has already demonstrated measurable results in production.

Today, AI-Sara already covers around 28% of IT consultation requests previously handled by the support team and serves as a foundation for further development of AI-driven IT Service Management.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The project aims to transform the modernization of legacy systems by using Generative AI to reverse-engineer source code, databases, interfaces, integrations, configuration files and technical dependencies, converting fragmented legacy knowledge into structured, traceable documentation and business specifications.

The objective is to significantly reduce the time, cost and human dependency involved in understanding legacy platforms while preserving critical business rules and system behavior. The resulting specifications become the foundation for designing modern architectures and generating new software with AI-assisted engineering, creating a controlled bridge from legacy code to modern platforms.

The approach seeks to make legacy modernization faster, more scalable, auditable and less dependent on undocumented institutional knowledge.

The innovation is not simply using AI to generate code; it is using AI to create a controlled knowledge and engineering layer between legacy systems and their modernization.

The solution establishes a continuous chain: Legacy Code → AI Reverse Engineering → Architecture & Dependency Model → Business Rules → Data Model → Functional & Technical Specifications → Modern Architecture → AI-Assisted Development.

AI analyzes heterogeneous artifacts and correlates source code, database structures, stored procedures, interfaces, configurations and dependencies to reconstruct how the system actually works. Human architects and business experts validate the resulting knowledge, creating governance and traceability before any new code is generated.

This approach converts undocumented legacy complexity into reusable engineering assets and creates a repeatable modernization factory rather than a one-time migration exercise.

The project established a repeatable AI-driven methodology for understanding and modernizing legacy systems, transforming source code and fragmented technical artifacts into structured architecture documentation, data models, business rules and validated functional and technical specifications.

It significantly accelerated the discovery and documentation phase, reducing dependence on scarce legacy-system experts and converting previously undocumented knowledge into reusable engineering assets. The approach also created traceability between legacy behavior, business requirements, specifications and future implementations.

By separating AI-driven analysis from human validation and governance, the project established a controlled foundation for AI-assisted modernization, reducing the risk of losing critical business logic during migration.

Most importantly, the project created a scalable modernization model that can be reused across different legacy applications.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

The goal of the project was to build a modern, cloud-based digital foundation for Thal Limited that could support current business needs and future growth. The project aimed to migrate the core ERP environment to SAP S/4HANA RISE Cloud, improve system reliability, strengthen business continuity, and create a scalable platform for group-wide operations across 12 company codes. It also focused on introducing AI through SAP Joule, enabling faster access to business information, and improving user productivity. Another key goal was to provide leadership with real-time visibility through SAP Analytics Cloud dashboards and to simplify financial consolidation through SAP Group Reporting. Overall, the project was designed to reduce manual effort, improve decision-making, strengthen governance, and prepare the organization for future innovation.

This project is unique because it combined cloud ERP, artificial intelligence, executive dashboards, and automated group reporting into one connected transformation. Thal Limited did not only move SAP to the cloud; it also used the opportunity to modernize how the business works, reports, and makes decisions. The implementation covered 12 company codes, making it a group-wide initiative with strong business impact. SAP S/4HANA RISE Cloud created a scalable and reliable digital core, SAP Joule introduced AI-assisted user interaction, SAP Analytics Cloud provided real-time leadership dashboards, and SAP Group Reporting automated financial consolidation. This end-to-end approach made the project more than a technology upgrade—it became a business transformation platform for faster decisions, stronger governance, better visibility, and future innovation.

 

The project delivered a modern, cloud-based and AI-enabled SAP platform for Thal Limited. It improved system reliability, scalability, and business continuity by moving the core ERP environment to SAP S/4HANA RISE Cloud. SAP Joule introduced AI-assisted interaction, helping users get information faster and work more efficiently. SAP Analytics Cloud dashboards gave leadership real-time visibility of key business areas including finance, sales, supply chain, production, workforce, and health and safety. SAP Group Reporting improved the financial close process by automating consolidation, reducing manual effort, eliminating inter-company transactions, and increasing reporting accuracy. Overall, the project enabled faster decision-making, stronger governance, improved operational efficiency, and created a future-ready digital foundation for continued innovation across the organization.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

NTU Pass aimed to replace fragmented physical-card and access processes with a unified digital identity and access platform for NTU’s students, faculty, staff, residents, contractors, collaborators and visitors. Its objectives were to modernise ageing infrastructure, consolidate 19 legacy access systems, integrate more than 10 enterprise systems, automate onboarding and access provisioning, strengthen security and governance, improve operational visibility, and reduce physical-card production. Redesigned user journeys included immediate issuance of digital credentials, default access from day one and 24/7 self-service residential hall check-in. The strategic outcome is a scalable digital identity foundation for future services across NTU’s three campuses.

The project united mobile credentials, infrastructure renewal and process redesign at campus scale. A single credential supports in-person identity verification, facility and residential access, library entry and borrowing, key-management cabinets and managed printing. Digital credentials and default access are available from day one, while 24/7 self-service hall check-in removes reliance on card production, key-fob collection and office hours. Delivery also stood out: competing solutions were installed and tested in live campus settings before contract award using a Validation of Specifications approach, identifying integration, hardware and operational risks early. The programme is progressively replacing 19 legacy access systems with a single governed platform, maintaining services throughout the transition across buildings of varying ages and technical standards.

(Delivered during: 1 Oct 2025 – 1 Nov 2026)

• Consolidated 8 of 19 legacy access systems into single platform

• Upgraded more than 7,000 access points across campuses

• Onboarded more than 61,000 users to NTU Pass

• Avoided printing over 22,000 physical ID cards

• Enabled digital credentials and default access from Day One for new users

• Introduced 24/7 self-service hall check-in, eliminating dependence on physical key-fob collection and hall office operating hours.

• Successfully conducted large-scale self-service hall check-in for approximately 2,000 students in July 2026

• Re-engineered processes supporting:

  • identity verification

  • facilities access

  • residential access

  • library services

  • key management

  • managed print

• Established centralised monitoring, audit logging and access visibility

• Enhanced security through device-bound credentials, biometric protection and remote credential management

• Improved productivity and operational efficiency through automation, process standardisation and platform consolidation

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Replace manual logbooks and shift reports with automatic, real-time measurement of the company's milling and packing operations. Objectives:

• calculate OEE (availability, performance, quality) automatically every shift.

• track yield and extraction against every active production Job Order.

• inspect every moving bag on the packing lines inline by computer vision and reject defective bags without stopping the line.

• alert the responsible teams in real time to prolonged stoppages, abnormal extraction rates and quality failures.

• link operational data to the corporate ERP environment so production performance is measured, attributed and reported without human transcription.

Most milling operations still reconstruct performance after the fact from paper logbooks. This project replaced that with automatic measurement at production speed. Its most distinctive element is inline quality inspection by computer vision, implemented and running in production since the first Q2 2026: a live stream is analysed continuously for packaging anomalies, printing errors, missing or empty date codes and structural defects on moving bags; a defect triggers an inline rejection that isolates the bag mechanically while the reason is logged automatically. That is inspection of every bag at line speed, not sampling after the fact. Around it, an automatic OEE engine and order-based yield tracking make every loss visible by cause and every kilogram accountable against its Job Order, on one live screen across the mills, the feed mill and the packing lines.

Measured on the live platform (81.56% availability, 77.91% performance, 100% quality), zero scrap with 880 units diverted to rework equal to 0.16% of output, 98.92% yield with a 75.28% extraction rate and milling loss of 1.08% against the 1.5% usual in commercial milling, and computer vision inspection live on five packing lines rejecting defective bags inline at production speed. Every loss is now attributed by cause; including 130 unclassified stops, had never been visible before. Nine workstations are monitored on one live screen, replacing manual logbooks, and the health and safety extension of the same platform is implemented and running. The OEE figure is the operation's first continuously measured baseline, so no before and after comparison is claimed.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

LTM is redefining how an enterprise scales by pursuing an ambitious goal: double revenue to USD 10 billion in five years—without doubling its workforce. At the heart of this strategy is a new digital workforce model, where AI agents work alongside people to transform how work gets done.

LTM has moved AI from isolated experiments into everyday enterprise operations, deploying 1,500+ AI agents as digital employees across IT, HR, Security, Project Delivery and Governance.

Technologically, LTM has established an enterprise-wide autonomous operations foundation on the ServiceNow AI Platform. Each AI agent is governed like a digital employee—with an identity, role, manager, training and performance review—bringing accountability into the agentic workforce.

Innovation is further strengthened through the AI Control Tower, creating unified AI inventory, risk oversight and governance across the digital workforce, with up to 80% projected improvement in AI asset management efficiency.

LTM is redefining how an enterprise scales by pursuing an ambitious goal: double revenue to USD 10 billion in five years—without doubling its workforce. At the heart of this strategy is a new digital workforce model, where AI agents work alongside people to transform how work gets done.

LTM has moved AI from isolated experiments into everyday enterprise operations, deploying 1,500+ AI agents as digital employees across IT, HR, Security, Project Delivery and Governance.

Technologically, LTM has established an enterprise-wide autonomous operations foundation on the ServiceNow AI Platform. Each AI agent is governed like a digital employee—with an identity, role, manager, training and performance review—bringing accountability into the agentic workforce.

Innovation is further strengthened through the AI Control Tower, creating unified AI inventory, risk oversight and governance across the digital workforce, with up to 80% projected improvement in AI asset management efficiency.

The initiative has delivered enterprise-scale outcomes across productivity, employee experience, operations and governance. LTM scaled AI from individual use cases into everyday operations, deploying 1,500+ AI agents across IT, HR, Security, Project Delivery and Governance.

Employee outcomes were realized through RAIma, which reimagined enterprise service delivery for 87,000 employees across 47 countries. HR onboarding satisfaction improved from 4.7 to 5.0, while HR productivity increased by 16%. IT ticket volumes were reduced by 30%, enabling employees to access intelligent support without relying on traditional portals.

Operational excellence was achieved across IT, Security and Project Delivery. Incident disruptions were reduced by 23%, while mean time to restore unplanned outages improved by 72.3%. Security Operations reduced incident assignment time to less than five seconds and enabled a 160-person team to absorb 40% more workload.

Compass 2.0 unified five applications into a single

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Unlike in retail banking, reviewing a loan application of medium and large corporates requires a credit analyst to review a large amount of credit documentation to prepare the conclusion on the request. This may include financial statements, business plans, charter documents, collateral documents, etc... The volumes may be up to 1000 pages and therefore this requires extensive manual efforts. Nowadays it has low level of automation and the review process can take weeks. Usage of GenAI agents to automate this process not only significantly reduces the costs but also speeds up the decision-making process, providing a competitive advantage in the market. CrediStreamAI solution that analyzes large volumes of corporate documents up to 1000 pages of documents and automatically generates pre-populated reports for credit assessments, legal due diligence, and collateral assessments. The system significantly reduces the manual workload for analysts (by ~ 4 man/days)

Credit Stream AI is the first agentic AI system in the Central Asian market, designed for industrial document digitization, data extraction, and analysis of unstructured information in the credit process. Credit Stream AI orchestrates agent-extractor, agent-critic, agent corrector and uses banks knowledge bases to prepare the conclusion. Individual processing stages were automated to a 95% degree, with an accuracy rate exceeding 95%. The project deployed and trained proprietary LLM models. On-premise GPU infrastructure allowed the solution to be deployed within the bank's secure environment, which is critical for handling sensitive client data and industrial scalability.

The solution is scalable across all ~600 branches in Kazakhstan and is used for corporate lending. The project covers several critical bank functions: credit, legal, and collateral analysis. Since just within first 3 months after project launch- 780 conclusions and reports have been prepared by AI agents for client applications each of the limits with > 1 bln tenge. For every conclusion ~4 man/days of credit analyst’s efforts were saved, i.e. total cost savings is about 3100 man/days or 12 FTEs equivalent of credit analysts.

— The project does not use solutions from the Global CIO catalog

— The project manager did not take part in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog

Transform the financial aid documentation journey from a fragmented, manual process into an intelligent, scalable, and student-centered digital operation.

The project aimed to centralize document submission, automate verification using AI, reduce errors and rework, improve transparency, and eliminate operational bottlenecks during seasonal enrollment peaks.

Additional objectives included reducing temporary staffing requirements and operating costs, strengthening compliance with program-specific eligibility rules, detecting potentially fraudulent documents, and protecting enrollment opportunities.

By combining AI automation with final human verification, the institution sought to increase operational capacity without proportionally increasing resources, while improving the applicant experience and supporting sustainable institutional growth.

Unlike basic document digitization, this project connects student enrollment events to an end-to-end, AI-assisted financial aid journey. A webhook triggers a personalized invitation to a white-label portal preconfigured with each program's required documents. AI checks uploads immediately; rejected files can be replaced on the spot, while accepted submissions proceed to human final review. Both students and back-office teams track progress in real time. Its distinctive feature is business-configurable intelligence: beyond built-in validations, teams describe new requirements to a Generative AI assistant that produces scripts for custom rules, including consistency checks across documents. Potential document fraud is also flagged for review. The approach combines rapid SaaS deployment, program-specific compliance, applicant self-service and human governance, making seasonal enrollment operations more scalable and cost-efficient.

The project delivered measurable operational and financial results, processing over 5,372 applicants, analyzing 116,019 documents and reviewing 342,007 pages with AI, achieving a 91% automatic approval rate.

Seasonal staffing requirements decreased from 37 to 22 analysts, a 40.5% reduction. First-year savings reached an estimated USD 34,840, with projected recurring annual savings of USD 50,368 from Year 2 onward, representing a 66% reduction in operating costs.

Beyond financial efficiency, the solution eliminated fragmented email-based document handling, enabled immediate AI validation and resubmission, and provided real-time visibility for students and back-office teams.

The institution gained a scalable, auditable process supporting four financial aid programs, reducing manual workload and rework while strengthening enrollment continuity, student experience and institutional growth.

— The project does not use solutions from the Global CIO catalog

— Profile in the ranking «Top 100 IT Leaders»

— The supplier profile is not present in the Global CIO catalog