Product

One workspace from employee question to policy proof.

RestrictAIChat combines familiar multi-model chat with policy, evidence, access, and spend controls that work in the same request path.

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One governed workflow

Files, model access, policy decisions, and audit evidence stay connected from request to result.

  1. Request

    Prompt with user, group, and model context

  2. Inspect

    Policy runs before any provider call

  3. Mask or block

    Sensitive matches leave as placeholders

  4. Approved provider

    Only the approved request crosses

Diagram of a prompt crossing a policy gate where sensitive content becomes a redacted block before reaching the provider. Policy: customer data guard Match masked before the call Decision recorded

Controls working together

Every control works in the same request path, so employees keep one simple workflow.

01

The workspace employees use

  • One multi-model workspace

    Give employees one place to work across approved models with policy applied automatically.

  • Four familiar chat experiences

    Let each person choose a familiar ChatGPT, Claude, Gemini, or Grok-style workspace.

  • Projects that keep context together

    Organize conversations and supporting context around ongoing team work.

  • Reusable team skills

    Reuse approved instructions so teams start from consistent ways of working.

02

Policy applied to every request

  • Policy in every request

    See the policy, route, and recorded outcome for each governed request.

  • Catch known sensitive data

    Detect known secrets and sensitive patterns before an approved provider call.

  • Understand policy intent

    Extend policy to context-sensitive requests with optional semantic review.

  • Govern files before sharing

    Extract text locally from supported files and apply the same governed request path.

03

What administrators control and prove

  • Approved models by team

    Choose which providers and models each tenant or group can use.

  • Shared spend controls

    Pool capacity across users and adapt model routing as team demand changes.

  • Review every policy outcome

    Review policy decisions and supporting audit evidence in one investigation flow.

  • Usage and savings reporting

    Show leaders usage, provider cost, routing outcomes, and recorded savings.