Immuta Brings AI to Data Governance, Launches Copilot

Data governance software provider Immuta today launched a new AI product designed to transform how data access and data governance is done. The company also launched the first product under the new Immuta AI brand, Immuta Copilot, which uses generative AI to write data access policies based on usage trends and metadata.

The GenAI revolution is exposing a lot of holes in the systems that companies use to manage and govern their data. As data demands go up, the manual processes that require humans to write data access policies can’t keep up, and neither can the rules-based ticketing systems that ostensibly help companies enforce those data access policies.

Immuta wants to reimagine the whole data governance process with Immuta AI. The company says the new offering, which it unveiled at the Gartner Data and Analytics conference taking place this week in Orlando, Florida, will function as a “foundational layer” within the Immuta Platform, and use a range of metadata to gain “a complete view of how data is accessed, used, and secured.”

“End-to-end visibility enables Immuta AI to make intelligent decisions about data access, going beyond simple rule-based systems,” the company says. “This allows customers to intelligently anticipate needs, proactively address risks, and truly scale data governance in the age of AI.”

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The first product in the Immuta AI catalog is Immuta Copilot. The new software is basically a policy writing assistant that allows users to describe the data access they want to enforce in plain language, says Immuta CTO Steve Touw. “Copilot will create a draft Immuta subscription policy, which, if activated, will push out access to data, from that description for you to review,” he tells BigDATAwire.

Under the covers, Immuta Copilot uses a range of different technologies. It uses a large language model (LLM) and vector search capabilities to understand natural language input and generate the data access policy. The product was trained on Immuta’s attribute-based access control (ABAC) policies, and generates policies that adhere to Immuta’s ABAC policy provisioning structure, he says.

Immuta Copilot also consumes metadata, including internal metadata, external metadata, identity metadata, and behavioral-based metadata. “That metadata sets the foundation for proposing policies to be enforced against those metadata abstractions,” Touw says.

Immuta Copilot will complement, rather than replace, existing rule-based systems, Touw says. Data owners will be among the biggest winners of Immuta Copilot, as it will allow them to create specific data access policies to handle data access for the data they own, without needing to have deep knowledge of all the metadata in their system, he says. In the future, Copilot will be able to create new rules based on historical trends in the approvals and denials to data products in the Immuta marketplace, he adds.

Three other Immuta AI products are in the works following Immuta Copilot. Additional products, which Immuta says will debut in the coming months, including access recertification, policy recommendation, and semantic discovery.

The future of AI isn’t just about better models, says Immuta Co-founder and CEO Matthew Caroll–it’s about better data governance.

“As enterprises scale AI adoption, now is the time to rethink how data is accessed, shared, and controlled,” Caroll says in a press release. “Traditional, ticket-based systems are already struggling to keep up, creating choke points that slow innovation and increase compliance risk. Soon, AI agents will act on behalf of human users, drastically multiplying access requests–far beyond what manual processes can handle.

“Governance must shift to dynamic, policy-driven automation that removes toil and scales enforcement at machine speed, Caroll continues. “This won’t replace governance teams–it will free them from tedious approvals so they can focus on strategy and oversight. With Immuta AI and Immuta Copilot, we’re laying the foundation for AI-powered governance that eliminates friction and meets the demands of AI-driven enterprises.”

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