CUSTOM RAG • HEALTHCARE

Clinical PubMed Knowledge Graph RAG

Sub-100ms enterprise medical search system querying 4.5 million PubMed articles with hybrid dense-sparse vector indexing and Cohere reranking.

Problem Statement

Over 5,000 medical researchers and oncologists needed instant verification of rare drug contraindications buried across 4.5 million PubMed clinical trial papers. Off-the-shelf LLM solutions suffered from severe hallucination risks and response latencies exceeding 4.5 seconds per query.

Solution & Architecture

Rohit implemented a **Hybrid Vector + Keyword RAG Architecture** with private vLLM inference:

  • Hybrid Indexing: Dense Qdrant vector embeddings combined with BM25 sparse keyword search for exact medical code hits.
  • Cohere Reranker: Filters top 50 candidates down to top 5 context chunks to ensure 99.4% precision.
  • vLLM GPU Acceleration: Fine-tuned open-weight Llama 3 70B hosted on private A100 GPU clusters delivering sub-85ms latency.

Verified Executive Review

"In medical research, hallucinated answers can be dangerous. Rohit designed a hybrid RAG system for our 4.5 million trial papers with zero hallucination rate and 82ms response time. Our 5,000 clinicians rely on Rohit's system daily. Exceptional engineering."

Lukas Weber

Metrics & Impact

99.4%
Retrieval Precision
82ms
Average Latency
Zero
Hallucinations

Project Specs

Category: Healthcare & Clinical AI
Status: Active Production
Architect: Rohit
Tech Stack Used
LlamaIndex vLLM Qdrant DB BM25

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