Healthcare12 weeks to production

Clinical Document Intelligence Pipeline

On-premise RAG pipeline processing 2M+ clinical documents with 94% retrieval accuracy. Full HIPAA compliance with zero data leaving the hospital network.

2M+

Documents Processed, Zero Exposure

Regional Health Network

The Challenge

A regional health network with 8 hospitals needed clinicians to find relevant patient history, research protocols, and compliance guidelines across 2M+ unstructured documents scattered across EMR systems, shared drives, and legacy archives. Average search time: 22 minutes per query. Clinicians were spending more time searching than treating.

Our Solution

Deployed an on-premise RAG system with document ingestion, chunking, embedding, and retrieval — all running within the hospital network. Role-based access ensures clinicians only see documents they are authorized to access. Every query is logged for HIPAA audit trails.

System Architecture

1

Document Ingestion

Processes PDF, DICOM metadata, HL7 messages, clinical notes from 8 source systems

2

Chunking & Embedding

Medical-aware text splitting with semantic boundary detection. Bio-medical embedding model fine-tuned on clinical corpus

3

Vector Store

On-premise Qdrant cluster with encryption at rest

4

Retrieval Agent

Hybrid search combining dense vectors, BM25 keyword matching, and metadata filters

5

Citation Engine

Every response traces back to source document, page, and paragraph

Results

94% retrieval accuracy on clinical queries
Search time reduced from 22 minutes to under 8 seconds
Zero data exposure -- all processing on-premise
Full HIPAA audit trail for every query
Adopted by 340+ clinicians across 8 facilities

Our clinicians got 22 minutes back per search. Multiply that by hundreds of queries per day across 8 hospitals.

Chief Medical Information Officer | Regional Health Network

Technology Stack

RAGOn-PremiseHIPAAQdrantFastAPIPython

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