Case study, RAG · Enterprise client
A RAG knowledge assistant that answers from company documents, with sources.
Staff ask questions in plain language and get answers grounded in internal documents, with every answer citing where it came from.
The problem
Knowledge was spread across policies, runbooks and service records. People spent hours searching or asking colleagues, and a generic chatbot couldn't be trusted because it might invent answers.
How it's built
- Retrieval-augmented generation (RAG) over the client's own documents, indexed with Azure AI Search.
- Azure OpenAI models generate answers only from the retrieved passages, and every answer cites its sources.
- Multi-agent orchestration to route and handle different kinds of questions.
- Microsoft Copilot Studio front end, so staff use it inside tools they already know.
- Entra ID single sign-on and role-based access, so people only see documents they're allowed to.
What shipped
An assistant with source citation, access control, audit logging and guardrails.
Clean handoff
Built with controlled access and audit logging so the client's own teams can run and extend it.
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