Slide decks covering identity, federation, tool governance, and AI governance patterns on Databricks.
Your organization needs an AI platform where business users ask questions in plain English and get governed answers from live data. Where knowledge workers search across documents and institutional memory using natural language. Where multiple AI agents collaborate (one retrieves data, another reasons over it, a third takes action), all coordinated by a supervisor. And where a tool layer connects these agents to your data, APIs, and business logic.
Internal teams will use it daily. But the harder ask is already on the table: partners, customers, and regulated subsidiaries need the same capabilities, through their own portals, authenticated by their own identity providers, without ever getting accounts on your platform.
Same data. Same AI capabilities. Same governance guarantees. Two completely different identity worlds.
On Databricks, this means Genie for natural language analytics, Vector Search for knowledge retrieval, Agent Bricks for multi-agent orchestration, MCP servers for tool governance, UC HTTP Connections for governed external service access, Unity Catalog for data access control, and AI Gateway for model traffic management. The three decks below show you how to govern all of it.
Serving Endpoints, Genie, UC Functions, Vector Search, UC HTTP Connections, Tables, Lakebase — auth model, identity flow, and gotchas for each.
Agent Bricks, MCP servers, UC Connections, token federation, AI Gateway, observability — end-to-end orchestration governance.