Overview
A UK-headquartered global financial group serving millions across banking, insurance, and open finance faced a common enterprise challenge. AI exploration was everywhere, but it lacked clear ownership, measurable ROI, and a path to scale:
- Data scientists were working in fragmented environments to build and test.
- Engineers spun up isolated AI tools with no shared standards.
- Business units had no secure channel for large-scale experimentation.
- Leadership saw token costs climbing without a clear ROI.
The result was a patchwork of initiatives, rising costs, and growing risk.
Challenge
An internal performance audit by the client’s team uncovered a strategic challenge: widespread but ungoverned usage of AI tools. Teams were duplicating efforts, and model deployments lacked governance.
The audit confirmed what some leaders already suspected: AI was maturing faster than the infrastructure and policies designed to support it. Executives recognized the urgency: Without intervention, the organization risked cost overruns and stalled innovation.
Solution
To ensure consistent, well-governed AI delivery across teams, the client needed a secure, standardized model for business and developer use. They engaged DataArt to create an internal AI platform that brought these initiatives together in a single, secure ecosystem.
This platform supported 73,000 users, giving controlled access to AI capabilities. Business users could query documents, extract insights, and automate information retrieval through a simple interface. Development teams gained a governed environment to safely experiment with LLMs, test use cases, and build prototypes without duplicating infrastructure. A custom memory optimization layer reduced token costs by avoiding redundant processing, and the entire platform was deployed inside the client’s infrastructure, eliminating external exposure.
With built-in auditability, OLAP integration, and readiness for enterprise systems, the client now has a scalable, secure foundation to support AI innovation across all functions, without sacrificing visibility, governance, or cost control.
Key Business Benefits
- Cost Optimization: Custom memory management drastically reduced unnecessary LLM token consumption, lowering operating costs while maintaining performance.
- Faster Decision-Making: Non-technical users can now securely upload documents, ask questions, and extract insights, reducing hours of manual work to minutes.
- Enterprise-Grade Security: The platform operates entirely within the client's infrastructure, ensuring complete alignment with security policies and regulatory requirements.
- Unified AI Governance: All interactions are traceable, auditable, and governed via centralized controls, addressing compliance, risk, and IT oversight needs.
- Rapid Adoption with Low Friction: The intuitive UI and integrated backend allowed for rapid cross-team usage, with 3,500+ daily active users within weeks of release.
- Future-Ready Infrastructure: The system integrates with enterprise knowledge repositories (e.g., Confluence) and includes an internal router layer for flexible model orchestration.
