◉ The Platform · Agent-first. Data is just one of the surfaces.

The Unified Trust Layer for the agentic enterprise.

One Control Plane. Powered by a Unified Trust Layer. Built on AI-Native Metadata and Context. Every agent discovered, every decision traced, every action secured, at runtime, across any framework or cloud.

◉ Agent-first. Data governed as one of many surfaces.

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◉ Already in production at

Apple Comcast Nike Intuit Amgen Northwestern Mutual Autodesk Zillow iFood SunLife Apple Comcast Nike Intuit Amgen Northwestern Mutual Autodesk Zillow iFood SunLife

◉ The Architecture

Agents on top. Data below. Trust Layer in between.

Every agent request passes through the Unified Trust Layer before it reaches anything it acts on. The layer carries AI-Native Metadata with every request: agent identity, declared purpose, data lineage, live policy state. Not static roles. Context that moves with the agent.

◉ Agents · LLMs · Copilots

App layer

Custom agents

LangChain · ADK

Native

Snowflake Cortex

Agents · functions

Native

Databricks Genie

Agent Bricks

SaaS

Salesforce

Agentforce · ServiceNow

◉ Trust3 AI · Unified Trust Layer

Trust Agents · Catalog · PBAC · Policy Workbench · Observability

Warehouse

Snowflake

Lakehouse

Databricks

Open table

Apache Iceberg

+ 50 more

Files · APIs · DBs

◉ Source data · 50+ systems

◉ How it works

Agents need to act. The Trust Layer decides what they can.

Five things have to be in place before an agent can act safely at scale. This is the order.

01 · Foundation

Data access

Solve the data problem.

Trusted data, governed at the source, native masking, lineage, unified catalog.

02 · Access

Entitlement

Only what they're entitled to.

Access bound to declared purpose, not job title. PBAC + auto-expiring grants.

03 · Risk

Production-ready

Visibility + risk cleared.

Trustscore on every agent. No agent reaches production without it.

04 · Trace

Observability

Every action, replayable.

Every prompt, tool call, decision, captured live, audit-ready forever.

05 · In production

Supply chain authz

Identity carries through every hop.

As agents call MCP, A2A, gateways, identity + purpose propagate, three hops deep.

◉ Foundation ◉ In production

◉ The capabilities

Four capabilities. One Trust Layer.

Each one covers a specific failure point in the agent lifecycle. Together they close the full chain from agent identity to data access to protocol security, with no seams governance can slip through.

Data Access

Trusted data, governed at the source.

Row-level, column-level, and tag-based access control, no proxy hop
One policy enforced natively across Snowflake, Databricks, BigQuery, and 50+ more
Full audit log: every query, every platform, every principal

Agent Discovery

Find every agent. Across every framework.

Automatic discovery across Databricks, Bedrock, Copilot Studio, and custom builds
Shadow AI detected: unregistered agents flagged the moment they appear
Trust Score assigned to every discovered agent, updated continuously

Agent Observability

Trace every prompt, tool call, every decision.

End-to-end traces: prompt → retrieval → tool → response
Real-time detectors for PII leakage, scope drift, and behavioral anomalies
One-click evidence packs for EU AI Act, HIPAA, NIST

Agent Security

Purpose-based access for the agentic era.

Access scoped to declared purpose, not job title, with auto-expiring grants
MCP and A2A protocol security built into the Trust Layer
Runtime guardrails, kill switch, and tamper-evident audit on every agent action

◉ Protocol-Level Controls

Defense at the protocol layer.

Where agents talk to tools and to each other, governance has to follow them. Two purpose-built layers, working together.

MCP Security

Every MCP server, treated as untrusted by default.

Discovery + content firewall, strips injected instructions
Scope minimization with RFC 8693 token exchange
Per-agent allowlists with tamper-evident audit log

A2A Security

Identity that travels through the delegation chain.

End-to-end identity + purpose propagation, every hop
Automatic PII, PCI, PHI redaction on outbound messages
One trace across A2A, MCP, and direct LLM calls

50+ Native sources

10× Faster to production

↓84% Audit prep time

0 Latency proxies

◉ Customer voice

Operating across multiple clouds and data platforms, governance complexity has historically slowed our ability to operationalize AI. With Trust3 AI, we now have a unified trust layer that consistently governs both our data and AI systems, significantly accelerating enterprise-wide adoption while maintaining the strict security, compliance, and visibility standards required at our scale.
CIO, Fortune 50 Enterprise

◉ Industry recognition

Independently validated.

◉ Intellyx · 2026 Report

Unifying data and AI governance: the key to successful AI implementations.

An independent analysis of how Trust3 AI bridges the gap between fragmented data governance and enterprise AI adoption at scale.

Download the report

Key finding

Unified governance

Intellyx identifies Trust3 AI as a pioneer in bridging data and AI governance into a single, coherent platform.

Validated approach

Agentic governance

Autonomous Trust Agents recognized as a breakthrough model for real-time policy enforcement across multi-cloud environments.

Market context

AI Act readiness

Trust3 AI's compliance posture highlighted as enterprises navigate GDPR, HIPAA, and EU AI Act requirements.

◉ Before & after Trust3 AI

The shift from fragmented to unified.

Before Trust3 AI	After Trust3 AI
Fragmented, manual governance processes	Unified, automated governance platform
Reactive fixes for compliance and ethics	Proactive, embedded governance guardrails
Siloed teams and inconsistent policies	Collaborative, federated policy management
Delayed AI initiatives due to governance gaps	Accelerated, secure AI adoption
Limited visibility into data and AI usage	Real-time observability and explainability
Quarterly audit fire drills	Continuous, evidence-based compliance

◉ Key features

Built for the way modern data and AI actually work.

Agentic architecture

Specialist Trust Agents (Discover, Catalog, Policy, Review) handle continuous, scalable governance autonomously.

Unified catalog

A single view linking raw data to AI applications, the substrate of governed, AI-ready context.

Intent-based PBAC

Dynamic, purpose-aware access controls that automatically expire when the work ends, no orphan grants.

Policy workbench

Centralized natural-language policy authoring, federated and enforced across every connected platform.

Full observability

Track lineage, prompts, and AI decisions for complete auditability and explainability, by default.

Open connectivity

Zero-latency native integrations with 50+ data platforms, no proxies, no rebuild, no lock-in.

Vendor-agnostic

Works with Snowflake, Databricks, Iceberg, Anthropic, OpenAI, and your existing IAM and SIEM stack.

Enterprise scale

Battle-tested architecture from the engineers behind Apache Ranger and Apache Atlas, the access-control and metadata standards now running in thousands of regulated enterprise environments.