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Use Case

Forensic Evidence for Financial AI Agents

SEC, FINRA, MiFID II, EU AI Act — regulators arrived with teeth. AI Identity gives every agent decision a cryptographic, tamper-evident audit trail that your examiner can verify offline with an open-source CLI. No vendor trust required.

The Challenge

In finance, what you can't prove didn't happen. Regulators demand receipts.

Regulatory Mandates

SEC, FINRA, MiFID II, and the EU AI Act require documented oversight of automated decision-making. Manual processes can't keep up.

Tamper Risk

Standard logging can be modified after the fact. Regulators need proof that records haven't been altered — not just a promise.

Compliance Gaps

Your AI agents make thousands of decisions daily. You need to prove each one followed policy — retroactively, on demand, under audit.

How AI Identity Solves This

Cryptographic proof of every agent action, built for regulated industries.

HMAC-Chained Audit Logs

Every agent action is cryptographically chained. Any tampering breaks the chain and is immediately detectable — provable in court.

Automated Compliance Assessments

Run your agent fleet against NIST AI RMF, SOC 2, EU AI Act, and ISO 42001 frameworks. Get a score and remediation steps.

Forensic Export

One-click evidence packages for regulators. Timeline reconstruction, policy verification, and integrity proofs — audit-ready.

Real-Time Monitoring

Flag policy violations as they happen, not weeks later during an audit. Fail-closed enforcement means violations are blocked, not just logged.

See It in Action

Verify audit integrity and pull compliance data in a few lines.

Python
from ai_identity import AIIdentityClient

async with AIIdentityClient(api_key="aid_sk_...") as client:
    # Verify the audit chain hasn't been tampered with
    verification = await client.audit.verify_chain(
        agent_id="agent_8f3a..."
    )
    print(f"Chain valid: {verification.valid}")
    print(f"Records checked: {verification.entries_verified}")

    # Pull audit stats for compliance reporting
    stats = await client.audit.stats(agent_id="agent_8f3a...")
    print(f"Total events: {stats.total_events}")
    print(f"Denied requests: {stats.denied_count}")

    # Pull full audit logs for regulatory export
    logs = await client.audit.list(
        agent_id="agent_8f3a...",
        limit=1000,
    )
    print(f"Total auditable actions: {logs.total}")

Ready for examiner-proof AI agents?

We're onboarding design partners in regulated finance. Get hands-on with the forensic audit chain, shape the v1.0 spec, lock in preferred pricing.