Databricks built a RAG agent it says can handle every kind of enterprise search

Most enterprise RAG pipelines are optimized for one search behavior. They fail silently on the others. A model trained to synthesize cross-document reports handles constraint-driven entity search poorly. A model tuned for simple lookup tasks falls apart on multi-step reasoning over internal notes. Most teams find out when something breaks.Databricks set out to fix that with KARL, short for Knowledge Agents via Reinforcement Learning. The company trained an agent across six distinct enterprise se

Read at VentureBeat