Chat with Your Own Data
AI-powered chat on your company documents. Precise answers with source citations — secure, auditable, on Azure.
Your Company Knowledge Is There — but Nobody Finds It
Process manuals, contracts, SOP documents, customer data — everything sits somewhere in SharePoint, file shares, or databases. But when an employee has a specific question, they search for hours or ask colleagues. And every time someone leaves, the implicit knowledge of where things are leaves with them.
Traditional knowledge management systems (SharePoint intranet, wiki, Confluence) fail at adoption: nobody maintains them, nobody searches them systematically. The alternative: an AI chat that understands natural language questions, searches your documents, and answers with source citations.
Microsoft Foundry and Azure AI Search make this possible — with data that stays in your Azure tenant. No third parties, no data leakage risks. All that is missing is structured implementation.
ACTIVITIES IN DETAIL
DELIVERABLES
Use Case Definition: One scoped application such as HR handbook, SOPs, or contracts
Data Preparation: Document inventory, source container, and the scanned-PDF readability decision
Retrieval Architecture: Classic AI Search index against managed Foundry IQ, with the reason
Search and RAG Build: Hybrid index with semantic ranking, Foundry chat model as answer engine
Answer Behaviour: A source citation on every answer, and a tested “not in your documents”
Security: Managed Identity, RBAC, and document-level permissions via Entra ID groups
Evaluation: Groundedness, relevance, and retrieval measured against 20 real questions
Next steps after Chat with Your Own Data
A cleanly configured tenant is the foundation. These blueprints build directly on it
