Trust3 AI announced Trustscore, a quantified risk rating for AI agents. It gives compliance, security, and legal teams a single, auditable number to track, report on, and defend during regulatory review of AI agents running within an organization. With EU AI Act enforcement beginning in August 2026, enterprises have fewer than five months to demonstrate they can account for what their AI agents are doing and what sensitive data those agents touch. By providing automated discovery and a proprietary Trustscore, Trust3 AI equips organizations with the critical visibility required to understand exactly what their AI agents are executing and what sensitive data they access.
As enterprises rapidly deploy artificial intelligence, security leaders face a growing governance crisis. Security teams often lack insight into the independent actions of multi-agent systems and the highly sensitive information these agents process daily. Organizations require more than just basic network visibility. They need visibility into specific agents and the sensitive data they might be processing with a quantifiable risk score to ensure regulatory compliance and protect consumer data from unintentional exposure.
The Problem Compliance Teams Cannot Afford to Ignore
Enterprise AI deployments are outpacing the governance frameworks designed to control them. Compliance officers write policy documents. Developers build AI systems. These two processes rarely meet – until an audit forces the issue.
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A Fortune 500 financial institution recently discovered this gap under the worst possible conditions. The firm had deployed more than 300 AI agents across fraud detection, loan origination, and credit risk workflow. During a regulatory audit, internal teams found these agents had been logging and retaining sensitive customer data – including Social Security numbers, home addresses, and full transaction histories – with no access controls, no ownership assignment, and no audit trail. Manual discovery was too slow and too incomplete to satisfy regulators.
Trust3 AI replaced that manual scramble with automated agent discovery across the entire multi-agent environment, applied fine-grained access controls, and generated a Trustscore for every agent in production. The institution achieved audit-ready compliance without pausing operations.
“AI projects may seem to be safely grounded on the right data in the pilot phase, but once multiple agents proliferate in production, they will access and share sensitive data and secrets with each other in non-deterministic ways as they complete tasks. Agents need to be tightly bound to business objectives and given clear guardrails using a governance solution like Trust3 AI to prevent data leakage and exposure”.
– Jason English, Director and Principal Analyst, Intellyx.
Policy as Enforcement, Not a Document
What separates Trust3 AI from monitoring and observability vendors is where enforcement happens. Most AI governance tools report what went wrong after the fact. Trust3 AI enforces compliance before an agent reaches production – connecting the policy a compliance officer authors in plain language to a developer constraint that cannot be bypassed at build time. When an agent’s Trustscore falls below threshold, remediation is automatic, documented, and tied directly to the policy that triggered it.
“The gap we close is the one between a compliance and security officer’s intent and a developer’s implementation. When enterprises run hundreds of agents across multiple platforms, a policy document sitting in a SharePoint folder is not governance. Trustscore turns that document into a live enforcement signal—one that survives into production and holds up in an audit.”
— Neeraj Sabharwal, Co-Founder, Trust3 AI
SOURCE: PRNewswire