Agentic RAG
HoldTechniques
A multi-agent RAG approach where specialized agents coordinate retrieval, reasoning, and generation.
Why it's here
Placed in Hold: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 0 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 5Martin Fowler·6/16/2026researchHow Bayer Built a Reliable Agentic AI System for Preclinical Research
This case study describes PRINCE, a cloud-hosted platform built by Bayer and Thoughtworks to improve access to preclinical safety study data. The system evolved from keyword search into an agentic retrieval-augmented generation and Text-to-SQL assistant that can answer complex questions and draft regulatory documents, with engineering focused on transparency, recovery, observability, and human oversight.