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Saram ConsultingThoughts and strategies on the intersection of Biotech, Artificial Intelligence, and Regulatory Compliance.
Five cost-optimization principles — better defaults, routing, caching, lean context, and visibility — translated into a validated, audit-ready LLM gateway architecture for regulated life sciences. Compliance is not a bolt-on; it is the routing logic.
Read Article →A complete, production-ready tutorial for building a hybrid retrieval-augmented generation pipeline — vector search plus BM25 keyword matching — using four Docker containers, local embeddings, and any OpenAI-compatible LLM.
Read Article →Standard RAG chunking destroys SOP context. Here's the parent-child chunking architecture, dual-engine table extraction, and prompt engineering patterns that make regulatory document retrieval actually work.
Read Article →Five independent analyses converge on the same answer for life sciences quality documents — but the devil is in the phasing. A research-grade comparison of seven RAG architectures with benchmarks, cost data, and a decision framework for regulated industries.
Read Article →Neither RAG nor fine-tuning alone satisfies GxP compliance. The QA-RAG dual-track architecture achieves 0.717 context precision on FDA regulatory Q&A — here's how to build it.
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