◉ Customer stories

Agents in production. Not in slide decks.

The hardest part of agentic AI isn't building the agent. It's earning the trust to ship it. These are the teams who got there — Fortune 500 enterprises running AI at the scale and risk-level where governance failures show up on cable news. Names anonymized at customer request. The work is real.

◉ Real customers · real outcomes

Five enterprises. Different clouds. Different stacks. One trust layer.

Production deployments at Fortune 500 enterprises governing agents and data across Agent Bricks, Microsoft Copilot Studio, ServiceNow Now Assist, Snowflake, BigQuery, and hybrid cloud — with Trustscores updated in real time and risk committees that finally know what they're approving.

◉ Featured · Fortune 500 financial services

300+ agents. Discovered during the audit.

"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."

— Jason English, Director and Principal Analyst, Intellyx (on the case)
The setup
  • 300+ AI agents in production across fraud, loan origination, and credit risk
  • Logging sensitive customer data — SSNs, addresses, transaction histories
  • No access controls. No ownership. No audit trail.
  • Manual discovery couldn't satisfy the regulator
What Trust3 AI did
  • Automated discovery across the multi-agent environment
  • Fine-grained access controls per agent, per source, per declared purpose
  • Continuous Trustscore for every agent in production
  • Plain-language policy → build-time constraint, no SharePoint in between
The outcomes
  • Audit-ready without pausing operations
  • Every Trustscore tied to a specific policy — remediation auto-documented
  • Below-threshold scores trigger immediate, recorded interventions
  • Compliance officer's intent → developer's enforced rule
◉ Productized · Trustscore

A 0–100 risk grade for every agent in your environment. Recomputed in real time as behavior, data access, or tool inventory changes.

Four dimensions: Security · Safety · Compliance · Accountability. Tier agents. Compare them. Block them when they slip below threshold. Available via API for your risk dashboard, ITSM, and CI/CD pipelines.

◉ Fortune 100 fintech

Past the IAM ceiling.

Hit AWS hard limits on IAM. Replaced over-privileged roles with attribute-based access governed at scale.

The problem
  • Securing a complex, fast-growing data ecosystem became impractical
  • S3 coarse-grained controls were overly permissive
  • Hit AWS service limits for user, group, and role policies per IAM role
  • Over-privileged IAM roles were difficult to track or revoke
The outcome
  • Access controlled by user, group, and attribute — synced via the corporate IdP
  • Permissions evaluated dynamically per request, no static role bloat
  • Real-time visibility across thousands of tables
  • Manual provisioning processes eliminated
◉ Top 5 US healthcare retail

100s of GCP projects, 1 control plane.

Thousands of BigQuery tables across hundreds of GCP projects, governed without a ticketing queue.

The problem
  • 1,000s of BigQuery tables and columns across 100s of GCP projects
  • Time-consuming, error-prone manual data security processes
  • Dataset access requests piling up in an unmanageable ticketing queue
  • Compliance colliding with developer velocity
The outcome
  • Provisioning automated for every new project, dataset, and table
  • Consistent role- and attribute-based controls applied automatically
  • Operational bottlenecks eliminated, compliance on auto-pilot
  • Cost savings from targeted protection vs. blanket encryption
◉ Fortune 50 health services

HITECH-grade, column-level.

Healthcare-grade governance on Snowflake, with fine-grained controls down to the column.

The problem
  • Cloud transition supporting diverse healthcare data types at scale
  • Need for restrictions down to schema, table, and column
  • HITECH compliance and other regulatory mandates
  • Comprehensive auditing required for internal and external review
The outcome
  • Trust3 AI integrated with Snowflake for granular, policy-driven access
  • Comprehensive audit across every interaction
  • Rapid model development for billing, claims, and health-trend monitoring
  • Reduced breach risk with documented evidence each cycle
◉ Fortune 50 media + telecom

One trust layer across hybrid cloud.

Replaced a failed DIY governance approach with a single hybrid-cloud control plane spanning on-prem and AWS.

The problem
  • Customer 360 effort blocked by fragmented data access controls
  • Cloud migration to AWS required consistent security across hybrid environments
  • DIY approach to governance had failed under operational scale
  • IT bottleneck choking analyst access to the data they needed
The outcome
  • One platform managing security and access across every analytical app
  • Consistent enforcement across the hybrid cloud, no per-system rewrite
  • Customer 360 unblocked — without creating compliance risk
  • IT bottleneck eliminated, customer + employee experience restored

Want your story here?

Trust3 AI customers get co-marketing support, executive briefing access, and a direct line to our engineering team. If you're shipping with us, let's tell the world.

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