Secure In-House RAG Agent & Document Intelligence Engine
Orchestrating a zero-hallucination, private enterprise knowledge base using Azure AI Foundry.
The Friction
The client required a secure knowledge retrieval system that could digest massive volumes of multi-format company documents (PDFs, DOCX, XLSX, TXT) and answer complex employee queries. The data was strictly confidential, meaning no public internet queries were allowed. Hallucinations were completely unacceptable, and maximum grounding accuracy was the primary success metric.
The Neural Architecture
Developed a secure Retrieval-Augmented Generation (RAG) agent within the client's private Azure tenant using Azure AI Foundry, Azure OpenAI Service, and Azure AI Search. We implemented advanced PDF/document chunking pipelines, integrated semantic re-ranking for superior retrieval precision, enforced strict query grounding (system instructions forcing responses to rely only on the retrieved context), and disabled internet search fallbacks.
Tech Stack Deployed
Impact Report
- Achieved near-zero hallucination rates by strictly grounding answers in the vector index.
- Kept 100% of sensitive corporate data contained within the client's secure private Azure tenant, complying with enterprise data safety guidelines.
- Handled multi-format document ingestion (PDF, Word, Excel, CSV) via Azure Document Intelligence.
- Enabled instant, cross-department document search, returning grounded citations for every generated answer.