Platform / AI Governance
AI governance built in, not bolted together.
One governance model for everything — AI agents, MCP tools, iPaaS integrations, and data pipelines. Not a different governance model per product. The same access controls, audit trails, and compliance framework across all of it. One platform, one policy.
What it does.
Full platform observability
Every agent action, MCP tool call, and workflow run logged — who triggered it, what ran, what the response was. Full visibility across AI and integration in one place.
Data masking in workflows
Built-in data masking protects PII, PHI, and financial data as it moves through processes. Sensitive fields stay protected inside workflows without requiring custom logic in each step.
Workflow data visibility
See exactly where data flows inside a workflow — which systems it touches, how it's transformed, where it lands. Compliance teams can trace movement without digging through raw logs.
Centralized access across every service
One RBAC model for workflows, agents, MCP tools, APIs, and data pipelines. Dynamic auth for MCP handles identity at the tool level — one place to grant, revoke, and audit access across everything.
Audit logging, log streaming & retention
Every action traceable to a real user — detailed, explainable, and searchable. Retention policies you configure, with real-time streaming to Splunk, Datadog, or any SIEM your security team already uses.
Comprehensive compliance
SOC 1 & SOC 2 Type II, HIPAA, GDPR, CCPA, and EU-US, Swiss-US, and UK-US Data Privacy Frameworks — penetration-tested annually. Full audit reports, DPAs, and sub-processor lists in the trust center, with right-to-audit in Enterprise contracts.
Data residency, encryption & isolation
Regional hosting in US, EU, and APAC with data encrypted at rest and in transit. Dev, staging, and prod separated by approval gates — nothing reaches production without sign-off.
Serverless, elastic execution
No infrastructure to provision, no capacity to pre-plan. Governance scales automatically — the same audit trails and access controls hold at any scale.
- 150B+
- integrations executed per year
- 1BN+
- AI workloads run
- 100%
- execution uptime
“With Tray, we're now building agents that can troubleshoot access issues, automate provisioning, and reduce manual load on our IT teams. With a more agile and cost-effective integration strategy, Yext is now well-equipped to drive innovation, improve operations, and scale automation at an enterprise level.”
What you can build
How teams scale with AI Governance.
Real governance scenarios teams run in production — from AI agent deployment to compliance at scale.
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Stand up a Center of Excellence.
IT owns the governance layer — connectors, policies, approved patterns — while teams across the business build on top. One standard, many builders, no chaos.
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Decentralized development. Centralized controls.
Let every team build their own workflows and agents — in their own workspace, at their own pace. Access controls, audit trails, and approval gates ensure nothing goes rogue.
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Pre-approved assets teams can actually reuse.
Publish approved connectors, sub-workflows, and agent templates as composable building blocks. Teams ship faster; IT knows exactly what's in production.
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Monitor usage and demand across the org.
See which teams are running what, how often, and at what volume — across integrations and AI workloads. Capacity planning and compliance reporting from one place.
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Workspaces that match how teams work.
Stand up isolated workspaces per team, region, or function. Dev, staging, and prod separated by default. Collaboration within boundaries — not despite them.
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Audit-ready before the auditor calls.
Compliance reports, access logs, and data flow records available on demand. No scramble when the compliance team asks — the evidence is already there.
Why is AI Governance different?
Built different. By design.
One unified governance layer.
The same RBAC, audit trails, and access controls whether you're running a workflow, an agent, an MCP tool, or a data pipeline. Not separate governance bolted onto each product.
One execution engine.
Agents, integrations, data pipelines — same runtime, same SLAs, same observability. Not a different engine stitched together per workload.
Logs you can actually use.
Every action detailed, explainable, and searchable — not just stored. Stream in real time to Splunk, Datadog, or any SIEM. Your compliance team gets answers, not raw data.
Teams already running on AI Governance
Real results from teams running in production.
IT / Business Tech
Apollo's IT team was overwhelmed by tickets that scaled linearly with headcount. Existing AI vendors offered rigid, prebuilt agents — Apollo…
Read the story →
IT / Business Tech
Life360 runs a consumer platform with 88 million monthly active users and a growing internal team. Early attempts at single-purpose bots lef…
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IT / Business Tech
Peddle's IT team was manually provisioning users across 260+ apps for a fast-growing partner network — meanwhile sales and marketing were re…
Read the story →Frequently asked questions
Can we mask sensitive data in workflows? +
Yes. Built-in data masking strips or masks sensitive fields — PII, PHI, or any field you define — as data moves through processes, without custom logic in each workflow.
Where do I start if I need to prove compliance to my CISO? +
The trust center at /trust has the public-facing version. Contact us and we'll share SOC 1 & SOC 2 reports, DPAs, penetration test summaries, and sub-processor lists directly.
Can we stream audit logs to our own SIEM? +
Yes. Tray.ai supports streaming logs directly to Splunk, Datadog, and others. Your compliance data lives in your systems, not just ours.
How granular is the RBAC? +
Per-workspace, per-connector, per-connection, per-MCP-tool. You control who can call which tool, with which credentials, against which data. One access model covers agents, integrations, MCP, and APIs.
What data residency options are available? +
US, EU, and APAC regional hosting. Data encrypted at rest and in transit. On-premise connectors available for data that can't leave your network at all.
One platform
Built as one. Not stitched together.
Every capability runs on the same connector library, governance layer, and data model — designed together from day one.
See AI Governance in action.
Walk through a scenario from your stack with a Tray.ai expert.