Generative AI & LLMsClient: CarePulse Health Networks
Enterprise RAG & Private Clinical Assistant System
Engineered a private HIPAA-compliant RAG pipeline summarizing medical records for 4,000+ active doctors.
68%
Charting Time Saved
4,000+
Active Doctors
99.4%
Extraction Accuracy
The Enterprise Challenge
Physicians spent up to 3 hours daily drafting clinical notes and reviewing unstructured PDF health records, resulting in severe doctor burnout and delayed treatment decisions.
Engineered Solution
Built a private Retrieval-Augmented Generation (RAG) platform leveraging fine-tuned Llama 3 models and Qdrant vector databases in isolated confidential computing containers.
Verified Results & Impact
- Cut clinical charting time by 68%, saving physicians 2+ hours per shift
- Extracted lab telemetry across 100,000+ patient records with 99.4% accuracy
- Complete HIPAA & HITECH compliance with zero data leakage to external APIs
Technologies Employed
PythonLlama 3LangChainQdrantPineconeNext.js
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