Case Study
Turning Fragmented Data into Enterprise Intelligence
A global heavy-equipment leader set out to become an AI-first enterprise, but fragmented data, inconsistent metadata and siloed information flows made it difficult to generate trusted insights at scale. Infosys helped create a unified, AI-ready data foundation reinforced by enterprise AI governance, composable AI assets and multi-modal data products, enabling high-precision AI Companions, real-time insights and a pathway toward Physical AI.
Key Challenges
Fragmented Enterprise Data
Data across 12+ legacy ERP systems made unified analytics difficult and limited the ability to scale AI across the enterprise.
Inconsistent Governance and Accessibility
Inconsistent metadata, lineage and access controls increased governance risk and made trusted information harder to access.
AI Initiatives Stuck in Pilot Mode
AI proofs-of-concept lacked shared infrastructure and a standardized path for moving successful experiments into production.
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Talk To ExpertsThe Solution
Creating a Unified Foundation for Enterprise AI
AI-ready Data Foundation
- Unified more than 45,000 datasets and over 10 PB of enterprise data into a common foundation.
- Created more than 1,000 multi-modal data products to make information easier to discover and use.
- Used metadata-driven architecture and standardized data pipelines to accelerate onboarding and improve consistency.
Enterprise AI Governance
- Established quality, privacy and compliance guardrails across the AI ecosystem.
- Introduced continuous model-accuracy evaluation to strengthen trust in AI-generated insights.
- Created a scalable governance framework to support enterprise-wide AI adoption.
AI Companions and Future Physical AI
- Developed an AI query engine delivering conversational access to enterprise information.
- Deployed more than 100 AI Companions across business functions to support faster decision-making.
- Established a pathway toward equipment-centric Physical AI use cases, including the foundation for “Copilot on Wheels” and future autonomous machinery.
From Fragmented Data to Enterprise-wide Intelligence
- A unified data foundation brings structured, unstructured and multi-modal information together so AI solutions can operate on a more consistent enterprise context.
- Governance built into the platform helps improve confidence in AI-generated insights while supporting scalable adoption across business functions.
- Reusable AI Companions and emerging Physical AI capabilities create a foundation for extending intelligence from enterprise decision-making into equipment and operations.
Business Outcomes
92% +
accuracy in insight generation
85% +
improvement in business efficiency
50% +
boost in engineering productivity
100+
AI Companions deployed
Building a Foundation for AI at Enterprise Scale
The transformation establishes a unified foundation for moving AI beyond isolated pilots and into repeatable enterprise use. By combining AI-ready data, governance, reusable AI Companions and a scalable intelligence layer, the organization can generate trusted insights more quickly while improving productivity and decision-making. The same foundation also creates a pathway for extending AI into physical equipment and increasingly autonomous industrial operations.
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