Saram ConsultingThe 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.
글 읽기 →Saram 인사이트 (Saram Insights)
바이오텍, 인공지능, 규제 컴플라이언스의 융합에 관한 심층 전략 및 실전 아키텍처 분석.
Evaluating AI Agents in Life Sciences CSV: The Boring Framework That Actually Works
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.
글 읽기 →Engineering the AI Agent Harness: The Validated Architecture Behind GxP-Compliant AI
A deep technical reference for building the deterministic control layer that makes AI agents inspectable, auditable, and defensible in FDA-regulated life sciences environments.
글 읽기 →The AI Agent Playbook for Regulated Life Sciences: What Actually Passes Inspection
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.
글 읽기 →How Frontier Labs Are Really Fighting Hallucinations in 2026
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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