Collibra and Databricks Strengthen Partnership to Support Governed Agentic AI

New integrations bring enterprise governance, semantic context, and AI lifecycle visibility directly into the Databricks Data Intelligence Platform – enabling organizations to scale agentic AI with greater transparency, traceability, and control

Databricks, the Data and AI company, and Collibra, the enterprise AI control plane, today announced a significant expansion of their strategic partnership. Highlighting this milestone, Databricks has named Collibra its Governance Partner of the Year, recognizing Collibra’s excellence in delivering unified governance across the Databricks Data Intelligence Platform.

Through a new bi-directional integration with Unity Catalog and expanded capabilities spanning Genie and Agent Bricks, the two companies are making it possible for joint customers to operate AI at enterprise scale with the AI oversight, business context, policy guardrails, and traceability that production demands.

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The expanded partnership builds on Collibra’s recent launch of the AI Command Center, a single place to govern every AI agent across the enterprise. Collibra is an Agent Bricks launch partner, and its MCP Server is already live in the Databricks Marketplace. Both now feed directly into the AI Command Center, extending its oversight across the Databricks Data Intelligence Platform, so the context and policy governed once in Collibra apply wherever data is activated: analytics, natural-language exploration in Genie, and autonomous agents in Agent Bricks.

Bringing enterprise business context into the Databricks Data Intelligence Platform

Unity Catalog gives Databricks customers a powerful governance foundation for data and AI assets across the Lakehouse. Collibra complements that foundation, enriching Unity Catalog with the broader enterprise context layer – data ownership, quality certifications, regulatory classifications, and business definitions that span well beyond any single environment – so that the same governed understanding travels consistently across the full data estate.

By synchronizing this context directly into Unity Catalog and downstream into Genie and Agent Bricks, users and AI systems on Databricks operate with a richer, more complete view of what the data means, who owns it, and how it should be used.

Bi-directional integration with Databricks Unity Catalog

At the center of the expanded partnership is a new, bi-directional integration that keeps Collibra and Databricks continuously aligned. Governed metadata, semantic definitions, and policies move from Collibra into Databricks, while technical metadata, lineage, and observability signals move from Databricks back into Collibra. This integration ensures that Collibra’s business context and governance are instantly available within Databricks, giving users direct access to critical information like data sensitivity and ownership without switching platforms. It streamlines compliance and empowers responsible data use at the point of consumption. Syncing technical metadata and lineage back to Collibra delivers holistic oversight and traceability, even for users without Databricks access, resulting in unified governance and a consistent view of data across both environments.

• Governance and policy enrichment (Collibra → Databricks): Business descriptions, data ownership, certifications, quality signals, and policies defined in Collibra are pushed directly into Unity Catalog. This business context travels with the data, reinforcing consistent governance at the point of consumption.
• Semantic enrichment for AI (Collibra → Databricks): Data specifications, business context and semantics governed in Collibra can be deployed into Databricks to enable business-ready metric views and to ground Agent Bricks agents in verified, enterprise-approved definitions. AI systems inherit the curated meaning of the data, improving accuracy and reducing the risk of misinterpretation in natural language analytics and autonomous decision-making.
• Automated AI traceability (Databricks → Collibra): Collibra’s AI Command Center captures metadata, runtime lineage and additional signals providing organizations with continuous AI oversight, real-time visibility, and built-in trust signals across AI systems running on Databricks.
• Access Governance (Collibra – Databricks): Collibra enables our customers to simplify protecting sensitive data across a complex data landscape by managing access controls and masking data in Databricks.

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Operational Trust from Agent Bricks into AI Command Center

The AI Command Center already gives teams a trusted, continuously governed view of every AI agent – and now it captures how agents actually behave in production, too. By bringing live operational signals from Databricks Agent Bricks into the AI Trust Score, it enriches existing governance and assessments with real-time evidence of agent quality: daily pass rates from LLM judges checking groundedness and safety, AI UC-1 assessment status, and token-consumption trends that catch agents drifting off the rails before they cause harm. A fleet-wide dashboard surfaces what matters most – average Trust Score, overall pass rates, and unmonitored agents – so leaders spot risk early and scale AI with confidence.

Collibra Insights integration with Databricks Lakebase coming in October/November

Collibra is working on an integration with Databricks Lakebase to bring your Collibra analytical data directly into Databricks Lakebase where your data teams already work. The integration is designed to handle large volumes of data and retain full history, without impacting the performance of your Collibra environment. With direct access to your Collibra data inside Databricks, you can build the reports you need, join with other datasets, and power custom KPIs and dashboards – or go further with Databricks AI/BI Genie and AgentBricks for AI-driven analytics.

Turning unstructured data into AI-ready volumes in Databricks

Through a new integration with Databricks Unity Catalog, Deasy Labs, a Collibra company, turns enterprise unstructured data into AI-ready volumes. Deasy qualifies every file as relevant, unique, fresh, and safe, then writes a taxonomy learned from the data itself into Databricks as the volume’s schema. AI engineers build directly on a curated, ready-to-use volume, with sensitive content caught before it ever reaches Databricks and no separate schema project to define first. Together with Collibra’s governed metadata and policy controls flowing into Unity Catalog, organizations get a faster path from raw enterprise content to production AI across both structured and unstructured data.

Extending Collibra’s governed context layer into the Databricks agent ecosystem

As organizations move from experimenting with AI to deploying autonomous agents that take real-world actions – approving transactions, generating reports, triggering workflows – the context those agents rely on becomes a material business risk. An agent that acts on stale definitions, uncertified data, or incomplete lineage is an agent operating outside enterprise controls.

Collibra’s MCP Server addresses this by delivering governed metadata and business context to AI agents in real time. Customers are already using the MCP Server to power context-aware AI systems and agents, driving its rise to a top position in the Databricks Marketplace. With the expanded integration, Agent Bricks agents can query Collibra’s MCP Server to enrich their understanding of available tools and data assets – retrieving certified definitions, checking quality scores, and validating access boundaries as part of agent interactions. The result is agents that operate within approved enterprise guardrails, not outside them.

As the race to productionize AI accelerates, customers consistently ask us how they can better manage their data in order to build AI apps and agents that make a real impact on their business,” said Stephen Orban, SVP, Product Ecosystem & Partnerships at Databricks. “As a key Databricks partner, Collibra helps our joint customers do exactly that. We’re proud to recognize them as 2026 Databricks Data Governance Partner of the Year.

Scaling governed AI across the Databricks Data Intelligence Platform

The partnership directly addresses one of the most pressing challenges enterprises faces as they scale generative AI and agentic systems: maintaining governance, compliance, and trust without slowing down innovation. By weaving Collibra’s governance capabilities into Unity Catalog, Genie, and Agent Bricks, organizations gain a path to production AI that is auditable, policy-aligned, and grounded in verified business context – regardless of how complex their data estate or how distributed their AI initiatives are.

Being recognized as Governance Partner of the Year underscores our commitment to helping Databricks customers move from AI experimentation to production-grade reality,” said Chandra Papudesu, VP, Product Management at Collibra. “This partnership ensures that the governed business context, automated traceability, and trust signal our customers rely on are available exactly where they build—inside the Data Intelligence Platform.

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