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Use Case

Replay Any Support Conversation

AI support agents handle sensitive customer data every day. When something goes wrong, you need to prove what the agent actually did — not guess. AI Identity gives every interaction a tamper-evident, cryptographically-signed audit trail.

The Challenge

Customer support agents are one of the most common AI deployments — and one of the most risky.

PII Exposure

Support agents process names, emails, and payment info. One misconfigured prompt and customer data leaks to unintended endpoints.

Shared API Keys

Multiple agents share the same credentials. When one is compromised, they all are. No way to isolate or revoke individually.

Zero Audit Trail

When a customer complains about AI behavior, you can't prove what the agent actually did. No logs, no accountability, no defense.

How AI Identity Solves This

Four layers of protection for every support agent interaction.

Forensic Replay of Every Conversation

HMAC-chained logs + DSSE-signed session attestations capture every agent action. When a customer disputes a chat, scrub through the exact sequence and produce signed evidence regulators verify offline.

Per-Agent Identity

Every support agent gets its own cryptographic identity and scoped API key. When something goes wrong the audit trail attributes back to the responsible agent, not a shared service account.

Policy Enforcement at the Edge

Restrict PII-containing endpoints, tool calls, and topics. The gateway blocks violations before they reach the model provider — and writes the block to the audit chain.

Compliance Evidence Bundles

One-click export of audit chain + signed attestations + offline verify CLI. CCPA, GDPR Art. 30, SOC 2 CC7 — your auditor verifies the math without contacting our servers.

See It in Action

Register a support agent with enforced policies in a few lines of Python.

Python
from ai_identity import AIIdentityClient

async with AIIdentityClient(api_key="aid_sk_...") as client:
    # Register a customer support agent
    agent = await client.agents.create(
        name="support-bot-tier1",
        description="Tier 1 customer support — billing inquiries only",
    )

    # Enforce PII boundaries
    await client.policies.create(
        agent_id=agent.agent.id,
        rules={
            "blocked_endpoints": ["/api/internal/*", "/admin/*"],
            "max_tokens_per_request": 4096,
            "allowed_topics": ["billing", "account_status", "refunds"],
        },
    )

    # Every action is now auditable
    print(f"Agent {agent.agent.name} is live with policy enforcement")

Ready to put forensics on your support stack?

We're onboarding design partners in support automation. Get hands-on access, shape the v1.0 spec, and lock in preferred pricing.