The proof layer for every AI system that matters.
Constrix doesn't care which model you use, which framework you built on, or which orchestrator you chose. It sits at the runtime layer and seals every decision — including who made it — before it executes.
When an AI agent moves money, you need more than a log.
Financial regulators don't accept 'our logs show' as evidence. They accept cryptographic proof. Constrix produces that proof for every AI-driven trade execution, every customer data access, and every automated advice decision — sealed, tamper-evident, and structured for regulatory inspection without manual log review.
- Trade execution governance
- Customer data access control
- AI-generated advice compliance
- Fraud detection override protection
Clinical AI that a compliance officer can actually defend.
HIPAA doesn't make exceptions for AI-generated decisions. Neither does your hospital board after an incident. Every clinical AI agent that accesses patient data has a registered identity, a defined scope, and a sealed record of every action it took — proven, attributed, and defensible.
- Clinical decision support governance
- Patient data access enforcement
- Prescription assistance guardrails
- Research data compliance
Attorney-client privilege enforced at the architecture layer.
Every legal AI agent is registered with a defined scope — which matters it can access, which documents it can read, which actions are denied. The delegation chain shows when one agent instructs another. Privilege boundary enforcement is structural and attributed.
- Privilege boundary enforcement
- Document classification compliance
- Opposing party data isolation
- Matter-level access control
Your agents are autonomous. Their governance shouldn't be advisory.
An autonomous agent executing multi-step tasks with tool calls, API access, and external actions is the highest-risk AI deployment. Every step can propagate consequences the next step cannot undo. Constrix intercepts every tool call — including every MCP call — evaluates it against governance policy, and seals the outcome before execution. Fail-closed by default.
- Tool call interception and evaluation
- Multi-agent communication governance
- Resource access policy enforcement
- Escalation state management
Your internal AI should have the same governance as your external-facing AI. It probably doesn't.
Internal AI agents — coding assistants, document generators, search tools — accumulate over time. Projects end. Tools are replaced. Agents keep running. Ghost detection finds every dormant internal agent, alerts the owner, and auto-revokes credentials after the configurable dormancy threshold.
- Data classification enforcement
- Internal IP protection
- Role-based model access
- Compliance-ready audit logs