AIIR — AI Integrity Receipts

Generate → Verify anywhere → Add CI when needed

$ aiir --pretty
┌─ Receipt: g1-a3f8b2c1d4e5...
│  Commit:  c4dec85630
│  AI:      YES (copilot)
│  Hash:    sha256:7f3a8b...
└──────────────────────────────

$ aiir --verify .aiir/receipts.jsonl
✅ Receipt g1-a3f8b2c1... VALID
   Hash matches. 0 tampering detected.
   Receipt core is intact.

# .github/workflows/aiir.yml
- uses: invariant-systems-ai/aiir@a54fe440a2be18fe51ad30149f1bbab944d578e5 # v1
  with:
    output-dir: .receipts/
# → signed receipts uploaded as artifacts

Try the browser verifier → — paste any JSON receipt, verification runs client-side. No upload. No account.

What AIIR Does and Does Not Do

How it works

Why not just commit trailers or git notes?

You could record AI involvement with Co-authored-by trailers, git notes, or ADRs — and AIIR is compatible with that mindset. The difference:

• Structured, machine-verifiable — receipts have a deterministic content hash. Change one byte and verification fails.
• Consistent across surfaces — the same format works in CLI, editor, CI, and AI assistants instead of ad-hoc free text.
• Optional signing — add Sigstore signatures in CI for cryptographic non-repudiation when you need stronger evidence.

Trailers and notes are the baseline. AIIR makes that baseline verifiable.

A real receipt

This is a sample receipt. Real receipts are deterministic for the same commit metadata; the page rotates demo values for presentation only.

┌─ Receipt: g1-a3f8b2c1d4e5f6a7...
│  Commit:  c4dec8563023
│  Subject: feat: add auth middleware
│  Author:  Jane Dev <jane@example.com>
│  Files:   4 changed
│  AI:      YES (message_match:co-authored-by: copilot)
│  Hash:    sha256:7f3a8b...
│  Time:    2026-03-07T09:48:59Z
│  Signed:  optional (CI / release)
└──────────────────────────────────────────

Who it's for

One Kernel, Multiple Trust Layers

Everything in AIIR hangs off one core: receipts plus verification. Assurance features and integrations sit around the same receipt format instead of redefining the product.

Detection is enrichment, not proof of hidden AI usage. The kernel remains the same: declared AI involvement, recorded as a deterministic receipt and verified independently.

Fits Into the Supply-Chain Tools You Already Use

AIIR is not pitched as a replacement for your attestation, provenance, or policy stack. The practical move is narrower: emit an AIIR receipt at the source boundary, then carry it into the systems you already trust to orchestrate, query, and enforce evidence.

Start with the full adapter lane at /ecosystem. It links the implementation notes, the public spec, the predicate reference, and the verifier into one public story.

Built for trust

Numbers you can verify. Every stat maps to a public CI run or an open-source file you can audit.

Last reviewed: 2026-03-31 · Release Health → · Live dashboard →

Multiple operator surfaces, one receipt format

Start with the CLI, then add the surface that matches how your team works. Every path emits the same content-addressed receipt.

See all integrations → including Azure Pipelines, Bitbucket, CircleCI, Jenkins, and policy engines.

Quick start

# CLI — receipt your last commit
pip install aiir
aiir --pretty

# Receipt a whole PR branch
aiir --range origin/main..HEAD --pretty

# Sign receipts with Sigstore
aiir --sign --output .receipts/

# GitHub Action (CI gate — signing on by default)
uses: invariant-systems-ai/aiir@a54fe440a2be18fe51ad30149f1bbab944d578e5 # v1

# GitLab CI/CD component
include:
  - component: gitlab.com/invariant-systems/aiir/receipt@1

Full documentation →

Evidence levels, from declared signals to signed release proof

AIIR is easiest to adopt when teams are explicit about what each workflow proves. Not every repository needs the strongest evidence on day one, but every level should be named honestly.

See Docs → for the full evidence model and Verify → for the separate verification tiers.

Why this matters

AI tools are now part of ordinary development. Copilot, ChatGPT, Claude, Cursor, and others all feed into git commit, but the durable record is still usually thin: a trailer, a bot author, or nothing.

Sooner or later someone asks: "Which commits involved AI tools, and what can you actually prove from the record?"

AIIR answers that question for every commit with declared AI markers. One command. Zero runtime dependencies. Apache 2.0.

See how AIIR compares to other provenance formats in the landscape overview, or review the conformance guide to build your own verifier.

Standards-readiness

AIIR is a vendor-led open specification on a transparent standards track. We score ourselves weekly across five categories and publish the result here. The goal: a receipt format rigorous enough for IETF, CNCF, or NIST adoption.

Last reviewed: 2026-03-31 · Summary refreshed for v1.3.0 public surfaces

Full scorecard + 90-day gap roadmap →  ·  Release Health →  ·  Spec Governance →

AIIR is complementary to SLSA, in-toto, SPDX, and CycloneDX — not a replacement. Goal: de facto adoption now, formal standards-track readiness over time.

Need help or want to engage?

Company

Invariant Systems, Inc. is a Delaware C-Corp building verifiable computing infrastructure for AI systems.

noah@invariantsystems.io