Building Reliable Agentic AI Systems

martinfowler.com · 3 months ago · 36

Bayer developed PRINCE, an agentic AI system using Retrieval-Augmented Generation to help preclinical researchers query unstructured drug discovery data through natural language instead of keyword search. The system evolved through three phases (Search, Ask, Do) and uses multiple specialized agents orchestrated via LangGraph to handle complex queries while maintaining reliability through fallback mechanisms and careful context management. Researchers can now access insights from decades of PDF study reports and structured data silos that were previously difficult to search, reducing manual analysis time and enabling faster data-driven decisions in drug discovery.