AI governance for when the stakes aren't theoretical

Your agent is capable. It's confident. It just doesn't know your rules.

And when it makes a decision you can't explain, you're the one liable.

AI knows what HIPAA is. It doesn't know what HIPAA means for you.

Every agent improvises slightly differently. That's not governance.

When regulators ask what your AI knew, you need an answer.

Support for regulated environments

HIPAA · SOC2 · CHAI · NIST

Your governance. Their guardrails.

SCP streams your governance context—your policies, your boundaries, your compliance requirements—directly to your AI agents at runtime. They operate inside your rules, not their training data.

SCP Architecture: AI Agents layer, Supervisory Control Plane layer, Your Governance layer

The agent handles the work. SCP keeps it within your boundaries.

What changes

Without SCP With SCP
Agent improvises based on training Agent follows your policies
No proof of what it knew Full audit trail, every request
Behavior drifts between agents Consistent governance, every agent
Update the agent to change behavior Update context, agent adjusts instantly

Your industry. Your rules.

Healthcare

Your PHI handling policy. Your minimum necessary standard. Your clinical safety thresholds. Not generic HIPAA guidance.

Finance

Your risk tolerance. Your lending criteria. Your fraud escalation rules. Not textbook compliance.

Legal

Your privilege protocols. Your conflict checks. Your document retention policy. Not general best practices.

Under the hood

For teams that need to validate the architecture:

Your agents become thin clients. Governance lives in the control plane.

Your agents are making decisions right now.

Do you know what rules they're following?

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