Boston-based data security company Immuta has unveiled significant enhancements to its AI-powered data provisioning platform, targeting what the company identifies as a critical obstacle to enterprise artificial intelligence adoption: sluggish manual data access processes.

The new capabilities within Immuta's AI layer are designed to streamline how organizations manage data access requests, potentially reducing approval times from weeks to minutes while maintaining security protocols. The announcement comes as enterprises increasingly struggle to balance rapid AI development with data governance requirements.

"Traditional models weren't built for the volume and velocity of access demands created by AI," said Matt Carroll, Immuta's CEO. "The organizations that win in this next era will be the ones that can provision data safely and in realtime."

The timing of Immuta's announcement reflects a growing industry challenge. While many organizations have made substantial investments in AI infrastructure and talent, data access workflows often remain stuck in legacy processes designed for simpler IT requests.

According to the company, users frequently wait days or weeks as requests move through multiple approval layers and ticketing systems originally built for hardware and software management.

These delays have created what Immuta characterizes as operational drag that particularly impacts AI initiatives, where both human analysts and automated systems require faster, broader access to datasets.

The platform update introduces three primary capabilities aimed at automating data access decisions:

Review Assist automatically evaluates incoming data access requests, assigning risk classifications of low, medium, or high based on historical approval patterns, user roles, and policy sensitivity. Each classification includes AI-generated explanations to help reviewers understand the automated assessment.

Data Unmasking Request provides users with visibility into which portions of datasets are currently restricted by policy, allowing them to submit targeted requests to access specific masked data with business justifications attached.

Model Context Protocol Support enables integration with third-party AI agents and assistants, allowing these automated systems to request and manage data access independently, reducing human intervention requirements.

The emphasis on "agentic data provisioning" reflects industry trends toward automated decision-making systems, though the practical implementation of such systems in highly regulated environments remains an evolving challenge across the sector.

The company plans to release additional features in the coming months as part of its broader platform evolution, though specific details about future capabilities were not disclosed in the announcement.

https://www.immuta.com/