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Saram ConsultingThoughts and strategies on the intersection of Biotech, Artificial Intelligence, and Regulatory Compliance.
In life sciences you cannot just show that an agent works — you have to prove it works the same way every time, trace why it answered, and have a qualified person review it. Here's how Langfuse Evaluation's four layers — Scores, Evaluators, Human Annotation, and Datasets — map directly to GxP compliance.
Read Article →Life sciences companies spend millions on commercial MDM suites they don't need. Here's the open-source architecture that delivers the same golden records, passes FDA audit, and costs a fraction — built entirely on PostgreSQL, Kafka, and commodity hardware.
Read Article →Multi-agent systems are the most overused and most misunderstood pattern in AI architecture. Most teams build them when a single agent with better prompting would outperform their five-agent Rube Goldberg machine. Here is how to design multi-agent systems that actually earn their 15x token cost — and how to know when you should not build one at all.
Read Article →Nadella just named the structural problem every enterprise AI deployment faces: you pay for intelligence twice — once with money, and again with the institutional knowledge you leak through every correction, trace, and eval. Here's the architecture to fix it.
Read Article →A week's worth of deep technical work — 20 posts covering RAG architecture for regulated documents, the MCP gateway pattern, multi-agent hallucination defense, LLM caching economics, and a rigorous stress-test of Google's Open Knowledge Format for life sciences quality systems.
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