The Reference Architecture for AI Agents in Regulated Life Sciences
The 7-layer reference architecture that turns individual AI compliance components into one integrated, inspectable, FDA-defensible system — from identity to evals.
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Saram ConsultingThoughts and strategies on the intersection of Biotech, Artificial Intelligence, and Regulatory Compliance.
The 7-layer reference architecture that turns individual AI compliance components into one integrated, inspectable, FDA-defensible system — from identity to evals.
Read Article →How to build deterministic evaluation systems for AI agents in GxP computer system validation — code evaluators, narrow judges, binary metrics, and datasets that survive FDA inspection.
Read Article →A deep technical reference for building the deterministic control layer that makes AI agents inspectable, auditable, and defensible in FDA-regulated life sciences environments.
Read Article →A comprehensive engineering and governance playbook for deploying agentic AI in GxP environments — risk tiering, GAMP 5 validation, ALCOA+ audit trails, and the anti-patterns that get 483s.
Read Article →The hallucination war has shifted from 'build better models' to 'build better systems.' Here's what OpenAI, Anthropic, DeepMind, Meta, and xAI are actually doing — and why none of it will reach zero.
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