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. With 20% turnover in mid-market companies, implicit knowledge is lost every time someone leaves.
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.
Azure OpenAI 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: scope a concrete application (e.g., HR handbook, SOPs, contract database)
Data preparation: document inventory, chunking strategy, metadata enrichment, OCR for scanned PDFs
Create Azure AI Search index: hybrid search (keyword + vector) with semantic ranking
Implement RAG pattern: Azure OpenAI as answer engine, AI Search as retrieval backend
Configure system prompt: enforce source citations, optimize groundedness, adjust temperature
Security: Managed Identity, RBAC, document-level permissions via Entra ID groups
Set up evaluation: measure relevance, groundedness, and completeness
Next steps after Chat with Your Own Data
A cleanly configured tenant is the foundation. These blueprints build directly on it
