🏛️ The Problem

AI agents make decisions that carry legal, financial, and safety consequences. Those decisions happen in memory, get logged in transient cloud infrastructure, and are tied to a runtime that may not exist when an auditor arrives six months later.

EU AI Act Article 12 requires providers of high-risk AI systems to maintain logs of operation appropriate to the system's lifecycle. FDA 21 CFR Part 11 requires tamper-evident audit trails. SOC 2 CC7.2 requires logging of unauthorized activity. None of these regulations define how evidence must be packaged for external review.

EPI closes that packaging gap.

💎 What EPI Does

EPI packages AI agent execution—the complete decision trail, governance evaluation, tool calls, inputs, outputs, approvals, and environmental context—into a single .epi artifact: a cryptographically signed, tamper-evident, self-contained forensic container.

The artifact can be emailed to an auditor, archived for 10 years, or opened on an air-gapped machine—without calling home, without the original runtime, and without trusting the producer.

The Forensic Container Architecture

agent_run.epi
├── [Envelope] EPI1 Header  — Binary magic, version, and payload SHA-256
└── [Payload] Signed ZIP    — Wrap with EPI1 Envelope
    ├── manifest.json       — Ed25519 signed root of trust + file hashes
    ├── steps.jsonl         — Immutable execution timeline (prev_hash chain)
    ├── governance.json     — The rulebook that governed the run
    ├── environment.json    — Host & Python runtime context snapshot
    ├── artifacts/          — Raw evidence preserved verbatim (e.g., AGT bundles)
    ├── viewer.html         — Self-contained offline forensic viewer
    └── VERIFY.txt          — Human-readable offline verification guide

🚀 Quick Start

pip install epi-recorder

1. Instrument an Agent

Capture any LLM-backed workflow with minimal boilerplate.

from epi_recorder import record, wrap_openai
from openai import OpenAI

# 1. Wrap your client for high-fidelity capture
client = wrap_openai(OpenAI())

# 2. Record the forensic context
with record("loan-approval.epi", workflow_name="Credit-V4"):
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Assess applicant #421"}]
    )

2. Verify the Artifact

epi verify --strict loan-approval.epi

────────────────────────────────────────────────────
  EPI Verification Report (v4.1.0)
────────────────────────────────────────────────────
  Trust Level:  HIGH
  Signature:    VALID   (Ed25519)
  Integrity:    OK      (SHA-256 manifest, 23 files)
  Chain:        INTACT  (prev_hash verified, 47 steps)
  Identity:     KNOWN   (production-signer-v4)

  This artifact has not been modified since sealing.
────────────────────────────────────────────────────

3. Open the Offline Viewer

epi view loan-approval.epi
# Opens viewer.html in your browser — zero dependencies, offline-ready.

🔌 Integrations

EPI acts as a universal evidence layer for the entire AI ecosystem:

• LangChain: ChatOpenAI(..., callbacks=[EPICallbackHandler()])
• LiteLLM: litellm.callbacks = [EPICallback()]
• Microsoft AGT: epi import agt <bundle> — adapter for regulatory evidence.
• OpenTelemetry: setup_epi_tracing() — turn spans into signed artifacts.
• pytest: pytest --epi — automatic forensic evidence for failing tests.

⚖️ Regulatory Compliance Mapping

EPI produces evidence that addresses specific global regulatory requirements. EPI is not a compliance guarantee and does not provide legal advice. Whether the enclosed evidence satisfies a specific regulatory threshold is for the auditor or notified body to determine.

🏛️ Standards Alignment

• SCITT (IETF): EPI produces SCITT-compatible COSE Sign1 statements for transparency log anchoring.
• AIUC-1 (Compliance): EPI generates structured compliance audit evidence mapping to the six AIUC-1 risk domains for autonomous agent audits. See AIUC-1 Evidence Mapping for details.
• CycloneDX: Preserves CycloneDX SBOMs under artifacts/sbom/ for software supply chain transparency.
• in-toto (CNCF): Roadmap: Exporting steps.jsonl as in-toto link files for execution supply chain verification.
• Ed25519 (RFC 8032): All manifests are signed using industry-standard Ed25519 digital signatures.

🤝 Founding Pilot Program

EPI is seeking regulated enterprises to pilot AI compliance evidence packaging.

If you operate AI agents under the EU AI Act, FDA 21 CFR Part 11, or SOC 2, and you need portable, independently-verifiable evidence, we invite you to join our Pilot Program.

What Pilots Receive:

• Direct Integration Support: Hands-on assistance from the maintainers.
• Priority Roadmap Influence: Shape the standard based on your compliance needs.
• Founding Partner Recognition: Optional listing as an early adopter.

Contact: mohdibrahim@epilabs.org — Subject: EPI Pilot — [Your Organization]

📑 Documentation

• 📖 Protocol Specification: The technical wire format.
• ⚖️ Governance Guide: Managing rulebooks and evaluations.
• 🇪🇺 EU AI Act Prep: Evidence workflow guide.
• 🛠️ CLI Reference: Comprehensive command guide.

🛡️ Security Model