Bedrock Data, the platform provider for data security and AI governance, has announced AI-assisted remediation, which federates the work of fixing data exposure to the data owners across the enterprise. Bedrock Data discovers who owns each exposed dataset, opens a ticket for that owner in the Jira or ServiceNow workflow the enterprise already runs and supplies the context needed to fix it.
Bedrock Data has launched AI-assisted remediation, generally available today and included with the Bedrock Data platform.
The capability discovers who owns each exposed dataset, opens a ticket in Jira or ServiceNow, and supplies the context needed to fix it.
When the owner closes the ticket, Bedrock Data validates that the exposure is remediated and reopens the ticket if it is not.
In Bedrock Data's Enterprise Data Security Confidence Index, 76% of respondents said a lack of automation and too much manual work hold back data security.
In EY's 2026 AI Risk and Governance Survey, 85% of executives at companies using AI agents said some agents take important actions without real-time human involvement.
Security teams can extend or override default routing with rules written in natural language.
"Every enterprise has far more data issues than its centralized data security team can action. Until now, with data growing exponentially, risk accumulation and risk remediation were divergent curves. Data is the responsibility of the lines of business and the data organization, and remediation only scales when they own the fix," said Bruno Kurtic, CEO and co-founder of Bedrock Data. "Bedrock Data finds the owner, sends the issue to the tools they already use, answers their questions inside the ticket and verifies the result. Security teams keep control of the rules and the audit trail, and those curves no longer diverge because remediation now operates at scale."
"Data risk is my team's responsibility, but lasting fixes have to come from the teams who run the systems every day," said Manish Chandela, EVP Information Security, Risk and Privacy at Sportradar. "Seeing the risk is table stakes. Reducing it means getting thousands of issues fixed without breaking the business. Bedrock Data puts each issue in front of the right owner, with the context to fix it, inside the tools they already use, and then proves the fix held."
Bedrock Data findings create tickets and route them to owners: Bedrock Data AI examines each exposure and explains it in context, so the owner understands the problem without a manual investigation. Tickets use the format the customer configures, including custom fields.
Bedrock Data AI answers questions inside the ticket while it is open, for example, "Who has access to this file?"
Bedrock Data policy engine tracks the ticket to closure: When the owner marks the ticket resolved, Bedrock Data validates the fix. If the exposure is gone, the ticket stays closed. If the exposure remains, Bedrock Data reopens the ticket with the reason.
Bedrock Data can apply the fix directly. Customers can create a policy that revokes sharing on documents based on sensitivity and other criteria, without triggering a workflow, and notifies the data owner that the change was made.
Closing the loop changes what security leaders can show their board and auditors. Every exposure has an owner, a timeline and evidence that the fix held. Auditors working under PCI DSS 4.0.1 and SOC 2, and regulators enforcing NYDFS Part 500, expect that audit trail. IBM's 2026 Cost of a Data Breach Report found that organizations making extensive use of AI and automation in security operations had average breach costs $1.93 million lower and lifecycles 65 days shorter.
About Bedrock Data
Bedrock Data is a data security and AI governance platform built on an enterprise knowledge graph of the company's data: what it is, where it lives, where it came from, who can access it and how it is used. Bedrock Data builds and maintains that graph, its patented Metadata Lake, by discovering and classifying data in place across cloud, SaaS, AI and on-premises environments at petabyte scale, without moving data outside customer boundaries. Its open, API-first design delivers those facts to the tools already in the enterprise stack and makes them the basis for policy enforcement, AI governance and remediation workflows.
