Inside one of the first production deployments of Lakebase: LangGuard's agentic workflow governance engine

* Fewer than 10% of enterprises have successfully deployed autonomous AI agents at scale, primarily because agents bypass traditional security controls by generating their own logic at runtime, creating an invisible governance gap. * Databricks provides unified governance for data, models, and access policies through Unity Catalog and AI Gateway. LangGuard extends these platform-level controls with a runtime enforcement layer for agentic workflows—monitoring and enforcing policy across the end-to-end chain of actions, decisions, tools, and credentials. It uses a patent-pending GRAIL™ data fabric that captures every agent action into a live knowledge graph and evaluates every policy decision in real time, without impacting agent performance. * Databricks Lakebase, the industry's first fully managed, serverless Postgres database built on the lakehouse, is what makes this possible, providing elastic scale-to-zero compute, low-latency query execution for hot operational data, and instant database branching for safe governance policy testing.