Generative AI inside a HIPAA-compliant clinical platform — fine-tuned models and RAG pipelines that cut context-aware reporting time by a quarter.

The challenge

Clinical reporting is high-stakes text generation under regulatory constraint: how do you apply generative AI where an invented detail is a safety issue, and every byte of patient data is governed?

What we built

Fine-tuned LLMs with QLoRA where prompting alone fell short, LangChain retrieval pipelines to ground generation in the right clinical context, and engineered prompts tested against real reporting workflows. Around the models: HIPAA-compliant full-stack engineering — React/TypeScript frontends, Python microservices for AI orchestration, end-to-end encryption, real-time inference — and the MLOps to run it, with Kafka pipelines and Airflow-orchestrated workflows spanning ingestion, training, evaluation and deployment.