Deep dives on AI product ownership, enterprise RAG evaluation, agentic workflows, and shipping compliant GenAI systems across life sciences & healthcare.
Moving past naive cosine similarity toward hybrid search, page-level citation mapping, and rigorous evaluation dimensions.
In enterprise deployments across life sciences and legal operations, standard RAG pipelines often suffer from hallucination leaks, inaccurate chunking, and lack of citation traceability. This essay outlines the multi-stage evaluation framework required to achieve 97%+ retention in production.
In enterprise deployments across life sciences and legal operations, standard RAG pipelines often suffer from hallucination leaks, inaccurate chunking, and lack of citation traceability. This essay outlines the multi-stage evaluation framework required to achieve 97%+ retention in production.
Regulated environments like clinical trials and GxP manufacturing do not need open-ended chatbots. They need agentic workflows with explicit tool-use, human-in-the-loop approval gates, and deterministic audit trails.
Rolling out the GenAI SOP Assistant across 25 global manufacturing sites required more than technical architecture — it required user-centric design, wave-based activation, and building deep trust with shop-floor operators.
Traditional software metrics like uptime and latency are insufficient for GenAI products. AI Product Owners must master evaluation metrics like Context Precision, Hallucination Rate, and Out-of-Scope Leakage.