Enterprise AI Platform
Thousands of employees across the organisation were already using public LLM tools — ChatGPT, Gemini, Claude — with no oversight, no data controls, and no visibility into what corporate information was being shared externally.
The security and compliance teams had raised serious concerns, but simply banning AI wasn't realistic. The organisation needed a way to give employees access to LLM capabilities through a controlled, governed internal platform.
The challenge wasn't just technical. It required designing an architecture that could scale across the enterprise, integrating with existing knowledge systems, and building employee trust in the internal alternative.
- Designed the architecture for an internal AI platform
- Recommended Azure-based private access patterns for LLM usage
- Created centralized, controllable employee access
- Introduced guardrails to reduce corporate data leakage risk
- Connected retrieval systems to SharePoint-based knowledge sources
- Enabled AI search across millions of internal documents
- Trained employees to use the platform effectively
We designed a private, Azure-hosted architecture that kept all data within the organisation's existing security perimeter. No corporate data left the tenant boundary.
The retrieval layer connected to SharePoint, internal wikis, and document management systems — giving employees AI-powered search and conversation over their own knowledge base rather than generic internet content.
Guardrails were implemented at multiple levels: input filtering, output monitoring, and role-based access controls that determined what data each employee group could access through the AI interface.
We ran structured training sessions across departments, focused on practical use cases relevant to each team's actual work — not generic AI overviews.
Rolled out governed LLM access to 5,000+ employees in 12 weeks with zero data incidents. Internal knowledge retrieval latency dropped from minutes to seconds.
The platform was rolled out to over 5,000 employees across 12 weeks with zero data leakage incidents — every interaction was logged, monitored, and contained within the corporate boundary.
Internal knowledge retrieval that previously required manual searching across SharePoint and document stores was reduced from minutes of browsing to seconds of AI-powered conversation.
Employee adoption exceeded projections — usage of uncontrolled external AI tools dropped significantly as the internal platform provided a better, safer alternative.
The architecture became a reference implementation for the organisation's broader AI strategy across other business units.