Native policy enforcement
Apply policy-based controls natively inside each connected data platform so access is enforced where the data is served, not through a separate layer that can drift or lag.
Immuta is a data provisioning and governance platform that helps teams control access, provision data requests, and produce audit evidence across connected data systems. It supports both human users and AI agents with policy-based workflows.
Immuta is a data provisioning platform for governing access, approving requests, and producing audit evidence across a distributed data environment. The site positions it as a single platform for policy, provisioning, and proof, with workflows for governance, access requests, and compliance.
Its published pages emphasize native enforcement across data platforms, integration with identity and catalog systems, and support for both human users and AI agents. Immuta is designed to let teams define access policies once, enforce them in the connected platform, and keep a traceable record of requests, approvals, and access outcomes.
Apply policy-based controls natively inside each connected data platform so access is enforced where the data is served, not through a separate layer that can drift or lag.
Connect identity systems such as Okta, SailPoint, and Microsoft Entra ID, then use attributes, groups, and entitlements to make access decisions for humans and AI agents.
Scan and classify tables, files, and other assets using regex or AI-based logic, then recommend classifications and risk tiers that make data easier to govern.
Author subscription policies, guardrails, and fine-grained data policies without code, including row-level restriction, column masking, and purpose-based controls.
Evaluate requests in real time, route out-of-policy cases to reviewers, and grant time-bounded access at the source for humans or ephemeral access for agents.
Search activity, policies, requests, and approvals from natural-language questions, then generate audit packets and reports with the supporting evidence.
Centralize access policy authoring and enforce controls across multiple warehouses, lakehouses, and databases without maintaining separate rules in each platform.
Handle access requests from catalogs or marketplaces, evaluate policy and risk, and route exceptions to reviewers when a request falls outside policy.
Grant agents ephemeral access at question time, then remove exposure after the task is complete so access is limited to the needed window.
Answer questions such as who can access a dataset, why access was granted, which policies applied, and whether the access remains appropriate.
Generate evidence packets, reports, and access summaries that include approvals, justifications, source links, and time-bound access details.
Immuta’s sources describe it as a platform for governance, provisioning, and compliance across data ecosystems. It enforces policy-based access controls natively in the data platform, provisions access in response to requests, and keeps access continuously auditable.
The source pages show Immuta connecting to identity systems, data catalogs, business applications, AI agents, and multiple data platforms such as Databricks, Snowflake, Google BigQuery, Starburst/Trino, PostgreSQL, Teradata, Oracle, Azure Synapse, Azure SQL, SQL Server, Redshift, Athena, S3, and others.
Yes. Immuta’s pricing page is not available in the collected sources and returns a page-not-found message, so the site does not expose public pricing in the material provided here.
Immuta’s provisioning page says humans request access through catalogs and marketplaces, while agents request at question time. Requests are evaluated against policy and risk, then approved, denied, or routed for human review before access is turned on at the source.
The compliance page says Immuta can generate evidence packets and reports, answer questions in natural language, and keep access continuously certified across humans, agents, and services.