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Rexaris AI

AI governance: know what AI exists, decide what it may do, prove it

Governance fails when it lives in spreadsheets. Rexaris AI turns inventory, policy and evidence into one system that runs on the actual traffic.

Boards and regulators ask the same three questions: which AI systems are in use, what are they allowed to do, and can you show it. Most organisations answer with a survey and a policy PDF, both out of date by the time they are read.

Rexaris AI keeps a live registry of models, applications, agents and MCP servers with an approval status for each, enforces policies on managed traffic, and records every decision. Shadow AI discovered by your endpoint, DLP and SASE tools can be brought into the same registry, so managed and observed usage sit side by side.

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What a governance layer has to provide

  • A single registry

    Models, applications, agents, MCP servers and tools with owner, source, users, risk and policy status.

  • Deterministic policy

    Rules on users, groups, data classes, applications and providers that resolve to Allow, Mask, Block or Route.

  • Evidence

    An audit trail that answers who used which model, under which rule, at what cost, without an investigation.

  • Visibility beyond the gateway

    Integration with existing security tools to discover AI usage outside managed traffic. Rexaris does not claim to see every AI service on every device.

Governance capabilities in Rexaris AI

  • AI registry

    Approved, restricted, prohibited, shadow and observed entries across managed and discovered AI.

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  • Policy engine

    Conditions and actions that the security team can read, test and audit.

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  • Shadow AI integrations

    Ingest events from Check Point, Netskope, Microsoft Purview, Zscaler and similar tools (roadmap).

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  • Audit and FinOps

    Requests, decisions, tokens and spend per user, team, application and model.

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Frequently asked questions

Is this a GRC tool?
No. GRC tools manage frameworks and assessments. Rexaris AI operates on the AI traffic itself and produces the inventory and evidence that GRC processes need.
How does shadow AI get into the registry?
Through integrations with the security tools that already observe endpoints and network traffic. Those integrations are on our roadmap and are labelled as such; the registry and managed-traffic governance are available today.
Can business owners see their own AI usage?
Yes, usage, policy outcomes and cost are reported per department, application and agent, which is also the basis for budgets.
Does it help with the EU AI Act or ISO 42001?
It provides the inventory, controls and records those frameworks expect for AI systems in use. It is not a certification and does not assert compliance on your behalf.

Related solutions

From the blog

Start with an inventory

Route one team through the gateway and see which models, applications and data classes actually appear.

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