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The regulator doesn't care that your model performed well in testing

Compliance-Native
Architecture

If you cannot produce an immutable audit trail of every agent decision, you are non-compliant. We engineer compliance into the middleware - not as a checkbox, but as a structural constraint every agent must satisfy before acting.

SR 11-7 EU AI Act SEC Rule 17a-4 ECOA / FCRA OCC MRM HIPAA

Core Pattern

The Compliance Proxy Pattern

Every agent action - without exception - passes through a mandatory middleware layer before execution. This layer is the policy enforcement point for your entire AI estate.

AGENT
Requests action
OPA POLICY CHECK
Allow / Deny / Escalate
AUDIT LOG
SHA-256 hash chain
EXECUTION
Approved & recorded

Immutable Audit Trails

We deploy ClickHouse with OpenTelemetry instrumentation and SHA-256 hash chains to create a tamper-evident linked list of every LLM inference, tool call, and decision output. Fully compliant with SEC Rule 17a-4 WORM storage requirements.

{
  "event_id": "evt_7k2m9x",
  "timestamp": "2026-05-09T14:51:00Z",
  "agent": "loan_decision_v3",
  "action": "credit_assessment",
  "input_hash": "sha256:a7f3...",
  "output_hash": "sha256:b2c1...",
  "prev_hash": "sha256:9de4...",
  "policy_check": "PASSED",
  "approver": "OPA_v2.1"
}
SEC 17a-4 SR 11-7

Automated Explainability

We engineer structured Chain-of-Thought outputs and SHAP feature attributions that map directly to ECOA/FCRA enumerated reason codes. Every adverse action notice is automatically populated with regulator-approved explanations.

Debt-to-income ratio −32pts ████░░░░
Payment history (24mo) −18pts ██░░░░░░
Credit utilization −9pts █░░░░░░░
ECOA FCRA EU AI Act Art.13

OPA Policy Enforcement

Open Policy Agent rules encode your compliance requirements as machine-readable, version-controlled code. When regulations change, you update the policy file - not the model, not the agent, not the infrastructure. Policy changes deploy in seconds with full rollback capability.

deny[reason] {
  action := input.agent.requested_action
  action == "send_adverse_notice"
  not input.context.ecoa_codes_present
  reason := "ECOA reason codes required"
}

Human-in-the-Loop Gates

High-risk decisions are automatically escalated to human reviewers with configurable confidence thresholds, dollar-amount triggers, and regulatory category flags. No agent can autonomously cross a defined risk boundary without human approval and a documented override reason.

Loan decisions > $500K → mandatory human review
Confidence score < 0.85 → escalation required
High-risk AI Act categories → HITL mandatory

Regulatory Coverage Matrix

FRAMEWORK JURISDICTION COVERAGE STATUS
SR 11-7 / OCC MRM US (Federal Reserve / OCC) Model cards, validation, audit trails COVERED
EU AI Act European Union Risk classification, transparency, HITL COVERED
SEC Rule 17a-4 US (Securities) WORM storage, immutable records COVERED
ECOA / FCRA US (Consumer Finance) Adverse action reason codes COVERED
HIPAA US (Healthcare) PHI handling, minimum necessary rule COVERED

Are Your Agents Examination-Ready?

Most aren't. Our Regulatory MRM Gap Assessment simulates an actual OCC or EU AI Act examination - and produces the remediation roadmap to survive it.

Book Your Compliance Assessment →

Frequently Asked Questions

How do you make AI agents EU AI Act compliant?

We implement the Compliance Proxy Pattern, a middleware layer that wraps every agent decision in an immutable audit trail, automated explainability reports, OPA policy enforcement, and human-in-the-loop gates. This architecture maps directly to EU AI Act Articles 13–15 and Annex IV requirements.

What is the SR 11-7 framework for AI?

SR 11-7 is the Federal Reserve's guidance on Model Risk Management. It requires banks and financial institutions to validate, document, and govern all models, including AI agents. We build the compliance infrastructure so your AI systems are examination-ready before regulators arrive.

Can AI agents produce audit trails?

Not by default, most agent frameworks produce no immutable records. We instrument every agent with ClickHouse-backed audit trails that capture inputs, outputs, reasoning chains, confidence scores, and policy decisions. Every decision is traceable and tamper-proof.

What regulations apply to enterprise AI?

The major frameworks include the EU AI Act (risk classification + transparency), SR 11-7 (model risk management for financial services), SOC 2 Type II (security controls), SEC Rule 17a-4 (records retention), and ISO 42001 (AI management systems). The specific mix depends on your industry and jurisdiction.