Databricks
LangChain
Python
Azure
FastAPI
Enterprise RAG System
Production RAG pipeline indexing millions of unstructured documents for AI-assisted research.
The challenge
The team needed to make millions of unstructured tax and legal documents searchable by an AI assistant that could provide accurate, grounded answers with citations.
Solution
Built an end-to-end RAG pipeline on Azure and Databricks:
- Ingestion: Document pipeline with semantic chunking, metadata enrichment, and incremental indexing
- Retrieval: Hybrid dense + sparse search with cross-encoder reranking
- Generation: LangChain orchestration with hallucination guards and citation tracking
- API: FastAPI service with streaming responses
Outcomes
- Indexed 2M+ documents with sub-second retrieval latency
- 85% reduction in research time for subject-matter experts
- Hallucination rate below 2% on internal benchmarks