Built for sensitive AI workflows.
- Product teams adding AI features to SaaS workflows.
- Support, CRM, CX, and internal assistant workflows with sensitive text.
- Security, privacy, platform, and governance teams that need pre-execution evidence.
AI Control Layer
Stop sensitive data before it reaches an AI model.
Clariva helps enterprise teams check, clean, and control AI-bound requests before they are sent. If a request passes, it can continue. If it fails, it is blocked with a clear reason and reviewable evidence.
Designed to complement your existing stack.
- Works before model-provider execution.
- Adds control without replacing your application or provider.
- Creates evidence before teams expand sensitive AI usage.
- Not a substitute for your own legal, security, or procurement review.
Why It Matters
AI risk starts before the model runs.
The critical moment is when sensitive data is about to leave your application. Clariva introduces a control point before that happens.
Risk & Operational Challenges
How Clariva Helps
01
Sensitive text moves fast
Support tickets, sales notes, documents, and prompts can reach AI tools before teams can review how that data is being handled.
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Transform before exposure
Sensitive content is handled according to policy before it can be used by any model.
02
Logs are not enough
A usage log may show that AI was called, but not whether the request met policy before execution.
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Verify before execution
Clariva checks proof, policy, and request integrity before any provider route can run.
03
Approvals need evidence
Security, privacy, and legal teams need a repeatable way to inspect request behavior before expanding AI usage.
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Produce reviewable evidence
Every decision creates a clear, inspectable record for validation, audit, and expansion decisions.
FAQ Preview
Common evaluation questions
Where does sensitive text get transformed?
Clariva supports customer-side transformation and policy-driven sanitization inside the deployed control layer. The agreed workflow determines what is transformed before the request crosses each boundary.
What happens if verification fails?
The request is rejected with structured status and reason information instead of continuing to provider execution.
How much latency does Clariva add?
Latency is measured during evaluation for the selected workflow, policy depth, provider route, and audit requirements.
What Clariva Does
A control layer between your application and AI providers.
Clariva does not replace your application or model provider. It checks, cleans, and controls sensitive AI-bound requests before execution.
Clean sensitive data
Apply policy-bound handling before sensitive text reaches an AI provider.
Verify the request
Verify policy, proof, and request integrity before execution.
Allow or block
Send approved requests forward, or return a clear rejection with evidence.
Start With A Profile
Match the workflow to the right evaluation path.
Use the starter profile cards below to identify the closest path for the workflow your team wants to review first.
For product and platform teams.
Use Clariva where your product would otherwise call an AI provider directly.
For revenue and support workflows.
Evaluate controls around customer conversations, notes, tickets, and account context.
For stricter review needs.
Add deeper policy, provider routing, audit, access, and deployment review when the workflow requires it.
Evaluation
Request a focused evaluation.
Start with the workflow your team is most likely to route through Clariva, then inspect the matching request and evidence examples.
See how a request is checked