AI Identity

Identity, governance, and forensic accountability for AI agents.

Each agent gets a cryptographic identity, enforceable policies, compliance-ready audit logs, and tamper-evident forensic trails. The design constraint the whole system is built around: trusting AI Identity evidence must never require trusting AI Identity. Everything a relying party needs to check our records independently is openly licensed and runs offline.

Verify our claims without asking us

The audit records are Merkle-batched and the signed checkpoints are published, so you can confirm the evidence is real before you talk to anyone here.

# 1. Pull a signed checkpoint from the public feed — no auth, no account
curl -s "https://api.ai-identity.co/evidence-anchor/checkpoints?limit=1"

# 2. Verify an exported audit chain offline — zero dependencies, MIT licensed
python3 cli/ai_identity_verify.py chain export.json

# 3. Verify a Merkle inclusion proof against a signed checkpoint
python3 cli/ai_identity_verify.py inclusion-proof bundle.json

The checkpoint history is also mirrored to the evidence-anchor-mirror branch of this repo every six hours, with append-only enforcement — a rewritten batch, a vanished root, or a mutated envelope fails the run rather than overwriting the record. A checkpoint that verifies offline but is absent from the public feed is the tamper signal.

Standards

The record formats are not ours to define, so we contributed them upstream:

• OCSF — the attestation object and record_integrity profile are merged into OCSF 1.9. This repo is the reference implementation that produced them; the emitter writes the merged shape.
• CPEX — the OCSF audit plugin is contributed to IBM's CPEX gateway under Apache-2.0.
• CoSAI WS4 — the CMF ↔ OCSF cross-map and interop material lives in docs/cosai-ws4-ocsf-mapping/.

	URL
Dashboard	ai-identity.co
API Docs	api.ai-identity.co/docs
Checkpoint feed	api.ai-identity.co/evidence-anchor/checkpoints

Integrations

LangChain

AI Identity provides a drop-in LangChain integration, available as a standalone PyPI package:

pip install langchain-ai-identity

from langchain_ai_identity import create_ai_identity_agent

agent = create_ai_identity_agent(
    tools=[...],
    agent_id="<your-agent-uuid>",
    ai_identity_api_key="aid_sk_...",
    openai_api_key="sk-...",
)
result = agent.invoke({"input": "What is the latest news on AI safety?"})

Every LLM call is authenticated, policy-checked, and logged with a tamper-evident audit trail. See the langchain-ai-identity PyPI page for full documentation.

Offline Forensic Verification (CLI)

Auditors and incident responders can verify audit chain integrity offline — no network access or vendor trust required:

python3 cli/ai_identity_verify.py chain export.json

The CLI is a single-file, zero-dependency Python script that independently verifies HMAC-SHA256 hash chains exported from AI Identity.

What is in this repository

AI-Identity/
+-- cli/            Offline verifier and audit review CLI (MIT)
+-- sdk/            Python, TypeScript, and LangChain SDKs
+-- integrations/   CPEX OCSF audit plugin (Apache-2.0), contributed upstream
+-- docs/           OCSF and CoSAI mappings, OTel crosswalk, evidence-anchor trust model, specs
+-- landing-page/   ai-identity.co (Next.js, deployed by Vercel)
+-- marketing/      Published collateral
+-- scripts/        Validators, the evidence-anchor mirror job, repo hygiene checks

Where the platform lives

The control plane (API server, gateway, mandate service, dashboard, and deployment manifests) moved to a private repository in September 2026. It is proprietary; see LICENSE. Nothing a relying party needs in order to verify AI Identity evidence depends on it: the verifier, the record formats, and the checkpoint feed are all here or upstream in OCSF. Commit history from before the split still contains the platform source. That is deliberate: the repository was public so the code could be audited, and history is part of that record.

Running the verifier

python3 cli/ai_identity_verify.py chain export.json
python3 cli/ai_identity_verify.py inclusion-proof bundle.json

Chain verification is stdlib-only and runs on Python 3.9+. Signature checks on attestations and checkpoints use the cryptography package. See cli/README.md.

Running the tests

pip install -r requirements-dev.txt
pip install pytest httpx cryptography
ruff check . && ruff format --check .
pytest -v

Tech Stack

• Verifier: Python 3.9+ standard library; cryptography for Ed25519 signature checks
• SDKs: Python 3.10+ (httpx, Pydantic), TypeScript, LangChain (PyPI)
• CPEX plugin: Rust
• Record formats: OCSF 1.9 attestation object and record_integrity profile, DSSE envelopes, Merkle-batched checkpoints
• Site: Next.js on Vercel
• CI: GitHub Actions, Ruff, pytest, CodeQL, OpenSSF Scorecard, evidence-anchor mirror every six hours

Support and advisory

Bugs in the verifier, SDKs, or mapping documents go to GitHub issues. Help with your own system is a paid advisory engagement; request one at ai-identity.co/request-services. See SUPPORT.md.

License

Platform: proprietary — the API, gateway, dashboard, Mandate Service, and shared libraries are all rights reserved. The repository is public so the code can be audited, not reused.

Verification and integration surfaces: permissive — trusting AI Identity evidence must never require trusting AI Identity, so everything a relying party needs to verify our records independently is openly licensed:

Component	License
cli/ — offline verifier (ships in every Case File bundle) + audit review CLI	MIT
sdk/langchain/ — LangChain SDK (PyPI)	MIT
CPEX OCSF audit plugin — contributed upstream to IBM's CPEX gateway	Apache-2.0

Record formats follow open standards: our schema contributions are merged upstream in ocsf/ocsf-schema (OCSF 1.9). See LICENSE for the full terms.