Introducing Collibra Maestro: Automate governance operations, turning days of manual work into minutes

Agentic AI is scaling faster than most governance teams can keep up. A recent Harris Poll survey commissioned by Collibra found that nine in ten organizations are actively deploying autonomous AI agents. Yet many governance teams are still performing tasks like resolving conflicting definitions and onboarding assets manually, work that can take weeks per task. General-purpose AI assistants can't close that gap since they lack business context and guardrails. Collibra Maestro changes that, bringing AI-powered automation directly into governance work, including the ability to build your own AI agents that operate inside Collibra.

What’s new: Collibra Maestro

Collibra Maestro is Collibra’s integrated suite of AI-powered capabilities for automating governance operations and getting trusted context to every asset, model and agent, faster.

At its center are Maestro Agents, AI agents that work inside the Collibra Platform, answering questions and completing tasks using context embedded within Collibra to automate governance. Maestro Agents come in two forms: Maestro Agents come in three forms: system agents Collibra manages (e.g., Business Definitions, Data and Analytics Discovery, and Collibra Documentation), ready-made templates you can use as-is or tailor; and fully configurable agents your own team builds in Maestro Studio, a no-code builder for creating and managing Maestro Agents, choosing exactly which knowledge base each agent can draw from and what actions it's allowed to take.

Maestro Assistant is where all of this comes together for end users: a conversational interface, built into Collibra, where data consumers ask questions in natural language and even call a specific Maestro Agent by name or by its @handle, the same way you'd tag a colleague in a chat.

Collibra Maestro also includes Maestro Actions (formerly known as Collibra AI), pre-built AI utilities like writing assistance for all text fields and semantic mapping, that run without a conversation at all.

How Collibra Maestro helps

Manual governance operations don’t scale with the pace of agentic AI adoption. Every new data source, business term dispute or stewardship request competes for the same limited hours, and the backlog only grows as AI initiatives multiply across the business.

Teams have tried various solutions, including plugging the gap with general-purpose AI assistants, but those tools operate without business context or appropriate guardrails, producing answers that are inconsistent or simply wrong, and sometimes taking actions that create new risk instead of removing it.

Collibra Maestro was built to close this gap directly inside the platform, where trusted data already lives.

Problems it solves

Left unaddressed, that gap shows up in a few consistent ways:

• Governance backlogs that pile up because many operations still depend on manual, one-by-one effort
• General-purpose AI tools that answer confidently and act without business context or appropriate guardrails, creating new risk instead of removing manual work
• No practical way for business and governance teams to build their own automation without specialized technical resources
• Inconsistent answers, definitions and actions across teams and domains, since there's no shared, trusted source every agent draws from
• Teams turning to workarounds and outside tools, creating new risks, when sanctioned options can't keep up with demand

How Collibra Maestro works

Collibra Maestro is built on Collibra’s enterprise Knowledge Graph. Maestro Studio’s agent builder lets you define a configurable Maestro Agent’s basic information (name, description and a unique @handle), then write instructions that set its role, tone and guardrails. The AI-powered writing assistant, a Maestro Action, can draft both the description and instructions for you, using the agent's name and handle as a starting point.

From there, you choose the agent’s knowledge base by selecting specific views from your organization or applications. Separately, tools let an agent perform tasks, such as creating an asset, on a user’s behalf. Tools are human-in-the-loop by design: the agent presents a summary of what it intends to do and waits for explicit approval before proceeding.

Before publishing, you can test the agent in a live preview, set its welcome message, an identifying color and at least one example question, then define who can access and own it. Once submitted, a reviewer approves the agent before it goes live, at which point it’s callable from Maestro Assistant, either by its @handle or by name from an agent dropdown. Once published, agent owners can track usage analytics to see how their agent is being adopted.

Beyond building from scratch, Maestro Studio also ships with ready-made agent templates for common governance use cases:

• Data product agent: Turns a producer's intent into a fully governed data product, complete with data product ports and a data contract, through a guided conversation
• Business glossary assistant: Verifies what a metric or term officially means before it's used in analysis and surfaces conflicting definitions across teams
• Data issue manager: Converts a discovered data problem, definition conflict, duplicate or quality gap into a governed data issue asset and manages it through resolution.
• Duplication detection agent: Scans your glossary for duplicate or near-duplicate assets and recommends a canonical version for review

To jumpstart Maestro Agent creation, teams can start from any of these templates and adjust the knowledge base, tools and instructions to fit their own environment. Teams can also import an agent configuration from a YAML file, or build an agent conversationally through Maestro Assistant instead of stepping through the builder.

Why you should be excited

Data stewards: Hand off repetitive governance work, such as answering term definition questions, tagging missing metadata or creating assets, to a Maestro Agent, freeing up time for higher-value governance work

Governance and compliance leads: Build restricted Maestro Agents that only reference specific, certified sources and only take pre-approved actions, giving them a controllable, auditable way to scale governance capacity

Data and analytics teams: Stand up a focused Maestro Agent scoped to their Data Marketplace content, helping business users discover the right data products and falling back to a broader search when the answer isn't in its knowledge base

IT and platform admins: Spend less time fielding one-off agent requests, since business teams can build and maintain their own Maestro Agents inside Collibra's guardrails without a custom development project, and can track usage analytics to see how those agents are actually being adopted.

Use cases

Here's what that looks like in practice:

Data product creation

A data engineer points a data product agent at a cataloged table; it reads the existing columns, lineage and descriptions, checks for duplicates, then drafts a complete data product, port and data contract for review, turning what used to take days of manual documentation into a single guided conversation.

AI governance

A governance team preparing for its AI governance committee review uses a duplication detection agent to scan its AI use cases for duplicates, then extends it with assessment tools to draft the governance assessment for each surviving use case, turning what used to take an afternoon of manual review into under ten minutes.

Regulatory reporting

A regulatory reporting team builds a restricted "FinREP Assistant" agent, scoped only to specific data assets in the Finance community, so analysts get consistent, citable answers about regulatory definitions and can request new terms be created when gaps are found, all with human approval before anything is created.

Key takeaways

Collibra Maestro brings AI-powered automation directly into governance work, from ready-to-use and tailored Maestro Agents to pre-built actions like automated descriptions and semantic mapping. Every configurable agent's answers are bound by the knowledge base and tools you choose for it, and actions are designed with human approval built in. That combination is what turns governance operations that used to take weeks into work that takes minutes, getting trusted context to every asset, model and agent faster.

Where to learn more about Collibra Maestro

Customers can access Collibra Maestro today, including Public Preview availability for Maestro Studio and Maestro Assistant.

Check out the following resources to learn more about Collibra Maestro and building your own Maestro Agents:

• Product documentation: About Maestro Studio and Maestro Agents
• Blog: Data product agent: Turn a cataloged table into a governed data product

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  Simla Sivanandan

  Simla Sivanandan

  Senior Manager, Product Management

  Collibra

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  Zuzana Zatrochova

  Zuzana Zatrochova

  Senior Product Manager

  Collibra

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  Melanie Henry

  Melanie Henry

  Product Marketing Director

  Collibra