Regulatory Intelligence & Evidence Layer for AI Agents

Know your obligations under
[ Colorado AI Act ]

IRIS continuously understands what you're building, maps it to your regulatory obligations, and tells you what to do next — on any enforcement stack, including Microsoft AGT. Plugs into your existing observability stack — Langfuse, LiteLLM, and more.

GitHub stars PyPI version
$ pip install iris-security-sdk iris-security-cli && iris quickstart
# Optional: Claude integration via MCP
pip install "iris-security-sdk[mcp]"
$ pip install iris-security-cli
Successfully installed iris-security-cli-0.2.19
$ iris compliance check --framework soc2 --agent loan-processor
SOC 2 Trust Services Criteria for AI Agents
  SOC2-CC6.1 Logical access controls ... PASS
  SOC2-CC6.2 Authentication ............ PASS
  SOC2-CC6.3 Authorization ............. PASS
  SOC2-CC7.1 System monitoring ......... FAIL
  SOC2-CC7.2 Anomaly detection ......... PASS
  SOC2-CC8.1 Change management ......... PASS
  SOC2-A1.1  Availability ............... PASS
  SOC2-CC9.2 Third-party AI provider risk FAIL
6/8 PASS · free, offline, no account required
$ iris compliance check --framework colorado-ai-act --agent payment-agent
Colorado AI Act — SB 26-189
  CO-001     ADMT inventory ......... PASS
  CO-002     impact assessment ...... PASS
  CO-003     consumer notice ........ PASS
  CO-004     consent gate ........... FAIL
  CO-RR-001  record retention ....... PASS
  CO-DEV-001 developer docs ....... PASS
5/6 PASS · re-run with --fix
14
Frameworks mapped · 2 free today
Sub-ms
Cedar evaluation, in-process
Apache 2.0
Open source
# iris policy compile --agent loan-processor
# Compiling policy-intent.md → Cedar...

permit(
  principal == iris::Agent::"loan-processor",
  action == iris::Action::"call",
  resource == iris::API::"credit-bureau-api"
) when {
  context.region in ["us-east-1"] &&
  context.user_consent_logged == true
};

✓ Policy compiled. Enforcing at runtime.

AI agents are deployed.
Governance is not.

Teams are shipping agents that call APIs, access customer data, and make decisions in employment, housing, credit, healthcare, and insurance — without knowing what systems they have running, what those agents are allowed to do, or how to prove they exercised reasonable care when a regulator asks.

Colorado AI Act — updated May 2026

The law changed. The old June 30 deadline no longer applies — the new effective date is January 1, 2027. Requirements were narrowed, but the obligations did not disappear. You still must tell people when AI makes decisions about them. Consumers still have the right to appeal. Violations carry civil penalties up to $20,000 each. The safe harbor still exists — but only for organizations that can demonstrate reasonable care. Six more months is not permission to wait. It is time to build real controls.

Models can be restricted with no warning

In June 2026, a US government export-control action briefly restricted Fable 5 and Mythos 5; access was later restored. Governments and providers can change model availability without notice. If your agent hardcodes a model string, that breaks your production system. IRIS treats models as governed resources — declare allowed tiers, define fallback chains, flip a directive kill switch in Git, and your agent routes to an approved baseline on the next call. Read Anthropic's statement ↗

Where most teams are today

Ungoverned agents, no audit trail

Developers ship agents fast. Security and compliance find out later — if at all. When the law asks what your agent did, you have screenshots and spreadsheets, not enforceable policy.

  • No inventory of AI systems making consequential decisions
  • Model hardcoded in source — breaks when providers suspend access
  • No policy enforced before the agent acts
  • Nothing version-controlled that an auditor can verify
What IRIS gives you

Policy as Code — govern before execution

Register every agent. Write what it is allowed to do in plain English. IRIS compiles to Cedar and enforces policy on every LLM call — with an evidence trail your compliance team can actually use.

  • Agent inventory via AgentPassport — your first compliance step
  • Model registry + directive kill switches with auto-fallback
  • Plain English policy compiled to formally verified Cedar
  • Runtime enforcement before every call — fail closed in production

Declare. Compile. Enforce. HITL. Witness.

IRIS is what comes after Terraform — runtime governance, not deployment management. Each command describes what IRIS does right now.

01

iris declare

Declare what the agent is allowed to do. Creates the AgentPassport — owner, team, compliance scope, data classification.

02

iris compile

Write policy-intent.md in plain English. IRIS compiles to Cedar — formally verified policy in Git.

03

iris enforce

Verify runtime enforcement is active — Cedar evaluated on every call, not just at deploy time.

04

iris hitl

Human-in-the-loop approval for high-risk actions — queue, review, approve or reject before execution proceeds.

05

iris witness

Live attested feed of every policy decision — who acted, what was permitted, evidence logged.

06

iris certify

Prove compliance readiness — Colorado AI Act, SOC 2, GDPR, HIPAA, and EU AI Act assessment are free in Community; AIUC-1, ISO 42001, certify export, and auditor deliverables are Enterprise. Try it: iris compliance check --framework gdpr.

07

iris sentinel (Enterprise preview)

Continuous monitoring — drift, score degradation, cost anomalies, and ungoverned agents. Local polling runs today; Slack/email alerting and org-wide posture tracking are Enterprise.

Ask Claude to govern your agents
IRIS connects to Claude Desktop and Cursor via MCP. Ask Claude "which regulations apply to my agent?" and Claude scans your codebase, checks your compliance, and shows you exactly what to do — no CLI required.
pip install iris-security-mcp

Govern everywhere
your agents run.

GH

GitHub App (in development)

The IRIS Governance GitHub App — org-wide PR scanning with a merge gate — is in active development and not yet on GitHub Marketplace. Use the GitHub Actions workflow today for the same PR scanning.

MCP

Claude & Cursor

Connect via MCP. Ask Claude in plain English: "scan my codebase for ungoverned agents" or "which regulations apply to my hiring AI?"

CI

GitHub Actions

Use the reusable iris-governance.yml workflow to scan every PR and gate merges on critical findings — works today, no GitHub App required.

Write policy in plain English.
Enforce it everywhere.

01
Discover — find what's running ungoverned
iris scan --discover surfaces LLM clients and agent patterns in your codebase that lack a passport or policy. See what actually runs before you govern it.
02
Inventory — register agents in your fleet
iris register creates an AgentPassport — owner, team, compliance scope, allowed models. The inventory regulators ask for. Not a deployment manifest — a record of what runs.
03
Define & guard — policy enforced at runtime
Write policy-intent.md, run iris policy compile, then guard every call with IrisAnthropic or @agent.guard(). Cedar evaluates before execution — not after.
governance/agents/loan-processor/policy-intent.md
# Source of truth — plain English policy intent

This agent processes loan applications.
It may call the credit bureau API in US regions only.
User consent must be logged before any loan decision.
It must never call any API not listed here.

# Compile to Cedar:
# iris policy compile --agent loan-processor
governance/agents/loan-processor/policy.cedar — compiled by IRIS
# Generated by IRIS from plain English intent
# iris policy compile --agent loan-processor

permit(
  principal == iris::Agent::"loan-processor",
  action == iris::Action::"call",
  resource == iris::API::"credit-bureau-api"
) when {
  context.region in ["us-east-1", "us-west-2"] &&
  context.user_consent_logged == true
};

forbid(
  principal == iris::Agent::"loan-processor",
  action, resource
) unless {
  resource in [
    iris::API::"credit-bureau-api",
    iris::API::"anthropic-api"
  ]
};

# Committed to Git. Reviewed. Auditable. Enforced.
Formally verified · Sub-millisecond-class evaluation · Human readable Cedar by AWS ↗

Policy in Git.
Enforcement in code.
Trust verified.

Policy in Git — not in our cloud
Your policies live in your repository. IRIS never holds your policy data, agent configs, or prompts. The SDK runs fully local with zero network required for enforcement.
Open source — verify the engine yourself
The Cedar evaluation engine, policy compiler, and CLI are all open source under Apache 2.0. Read the code. Run the tests. Audit the compliance bundles.
Human in the loop — when it matters
When a governed agent attempts a high-risk action, IRIS pauses the call and notifies your team via Slack, email, or PagerDuty. One click to approve or reject. The agent waits. The full decision — who approved, when, and why — is recorded in the Evidence Vault with a tamper-evident approval token.
AIUC-1 evidence export + ISO 42001 mapping
AIUC-1 evidence export (B006-format) and ISO 42001 coverage mapping — derived from AIUC-1's published crosswalk, not independent interpretation. Export auditor-ready JSON keyed by AIUC-1 sub-control IDs (B006.1, B006.2, B006.3). The B006 export assembles AgentPassport configuration and Evidence Vault event samples directly.
Evidence Vault — append-only system of record
Evidence Vault v2 records every policy evaluation, HITL decision, and CI/CD run as an HMAC-signed, hash-chained event — tamper-evident by architecture. The default local path logs append-only JSONL for development; enable Evidence Vault v2 for signed, hash-chained tamper evidence. Record pipeline evidence with iris evidence record-cicd.
# Verify policy enforcement locally
$ pip install iris-security-cli
$ iris compliance check --framework colorado-ai-act
✓ Agent: loan-processor — PASS
✓ All 6 Colorado AI Act rules satisfied

Common questions.

Is IRIS like Terraform for AI agents?
No. Terraform governs what gets deployed — infrastructure, configs, resources standing up in an environment. IRIS governs what runs after deploy: which APIs an agent calls, which models it uses, whether each LLM request passes policy. Think of IRIS as what comes after Terraform — the runtime governance layer. iris scan discovers what's running, iris register inventories your fleet, and @agent.guard() enforces policy on every call.
Does IRIS require cloud infrastructure?
No. IRIS runs fully local. Cedar policy evaluation happens in-process with zero network required. You can govern agents on your laptop, in CI, or in production without any IRIS-hosted service.
What is Cedar and why does IRIS use it?
Cedar is a formally verified policy language from AWS, designed for authorization at scale. It evaluates in microseconds, is human-readable, and has mathematical proofs of correctness. IRIS compiles your plain English intent to Cedar so you never write policy syntax yourself.
How is IRIS different from LLM output monitoring tools?
Monitoring tools scan outputs after the fact. IRIS governs the full agent lifecycle — declaring what is allowed before execution, blocking violations at runtime, and maintaining an auditable policy history in Git. Detection tells you what happened. Governance determines what is allowed to happen.
How does Policy as Code help with a regulatory audit?
Policy as Code means your AI governance is version-controlled, reviewable, and auditable in the same way your infrastructure code is. When a regulator asks what your agent is allowed to do, you show them the Cedar policy in Git — a document with a reviewer, a timestamp, and a commit hash. Not a screenshot. Not a PDF someone generated. The actual policy that is actually enforced at runtime on every call.

IRIS also generates the evidence package: the audit trail, impact assessments, compliance check results, and certification readiness score. The auditor reviews it and signs off. We are honest about what IRIS handles and what your team handles.
What happens when a provider or government suspends a model my agent uses?
In June 2026, a US government export-control action briefly restricted Fable 5 and Mythos 5; access was later restored. Governments and providers can change model availability without notice. If your agent hardcodes a model string, that breaks your production system. IRIS governs models separately from APIs: define tiers and fallback chains in governance/models/registry.yaml, block models via directive kill switches in governance/directives/active.yaml, and IrisAnthropic auto-routes to your approved baseline on the next call — no redeploy. The event is logged to the Evidence Vault.
Did the Colorado AI Act change? What do I need to do now?
Yes. Governor Polis signed a replacement law on May 14, 2026. The effective date moved to January 1, 2027, and some requirements were scaled back — but notice, transparency, consumer appeal rights, and the reasonable-care safe harbor remain. Start by inventorying every AI system that touches employment, housing, credit, healthcare, or insurance decisions. IRIS gives you that inventory (AgentPassport), enforced policy (Cedar), and the evidence package auditors expect — locally, with no cloud required.
Do you cover AI in hiring and recruiting?
Yes. IRIS covers NYC Local Law 144 (the most actively enforced AI hiring law in the US), the Illinois AI Video Interview Act, and the employment-domain provisions of CCPA/CPRA ADMT and the EU AI Act. These are available in Enterprise. The free tier shows you the rules and your top gaps — Enterprise unlocks the full evidence package and certification report that an auditor or the NYC DCWP will ask for.
Does IRIS work inside Claude?
Yes. Install iris-security-mcp or pip install "iris-security-sdk[mcp]" and connect IRIS to Claude Desktop. Ask Claude in plain English: "scan my codebase for ungoverned agents" or "which regulations apply to my hiring AI?" Claude uses IRIS tools to answer with real data from your actual codebase.
Can we install IRIS from GitHub Marketplace?
Not yet — the IRIS Governance GitHub App (org-wide PR scanning with a one-click merge gate) is in active development and not yet published to GitHub Marketplace. Today, use the reusable iris-governance.yml GitHub Actions workflow for the same PR scanning: every PR is checked, critical findings block the merge, and the developer gets a comment with the exact one-line fix.
Can we have different compliance requirements per environment?
Yes. IRIS uses a dynamic environment model where your security team defines environments in iris-security.yaml and attaches compliance frameworks and enforcement levels to each one. dev might have no frameworks enforced. production-eu enforces GDPR and EU AI Act. production-fedramp enforces FedRAMP Moderate. Set IRIS_ENV in your deployment config and IRIS applies the right policy automatically.
What is the Evidence Vault and how is it different from a log file?
The Evidence Vault is an append-only ledger — not a rotating log. The default local path writes unsigned JSONL for development; Evidence Vault v2 adds HMAC signing and hash chaining so tampering with any event breaks the chain. Events can be mapped to compliance controls (Colorado CO-004, AIUC-B006, HIPAA-001, …) so one collection satisfies many framework reports. CI/CD pipelines record evidence with iris evidence record-cicd — even when the governance gate fails. See the Evidence Vault guide.
Does IRIS help with AIUC-1 certification?
IRIS generates AIUC-1 B006 readiness evidence (technical evidence only; certification requires an accredited auditor). AIUC-1 is a third-party certifiable AI agent standard — Schellman is the first accredited auditor. IRIS ships B006-format evidence export today as an Enterprise capability (iris certify --framework aiuc-1 --format aiuc1-export). IRIS generates technical evidence in AIUC-1's own evidence-ID format (B006.1, B006.2, etc.) for the controls IRIS's runtime enforcement directly produces evidence for — agent access restrictions, HITL review records, activity logs, PII leakage prevention. IRIS does not replace the accredited auditor or AIUC-1's required third-party adversarial and hallucination testing — those remain separate engagements.
Do you have paid tiers?
Not yet, by design. Community is free, open source, and fully real today — Cedar policy engine, HITL, Evidence Vault, GitHub integration, all of it. We are building Enterprise capabilities in the open and will turn pricing on once they are real, tested, and something we'd stand behind in a customer conversation — not before. Want to help shape it? Reach out as a design partner.
Which compliance frameworks does IRIS support?
14 compliance frameworks — Colorado AI Act (SB 26-189) is available in Community today via iris compliance scan, which maps your obligations across frameworks like GDPR, HIPAA, and ISO 42001 — no account required for local CLI use. SOC 2, GDPR, HIPAA, and EU AI Act are also free, fully offline assessments — iris compliance check --framework gdpr (or hipaa, eu-ai-act, soc2) runs the complete rule set with a local PASS/FAIL verdict; certify export, the deeper remediation report, and continuous monitoring stay Enterprise. EU AI Act's free check currently covers one rule (EU-AIA-14); GDPR and HIPAA cover 8 and 9 respectively — deeper EU AI Act coverage is on the roadmap. AIUC-1 B006 evidence export (aiuc-1) and ISO/IEC 42001 (iso-42001) ship today as Enterprise capabilities — not roadmap items. NIST AI RMF, FedRAMP, CCPA/CPRA ADMT (ccpa-admt), China PIPL (china-pipl), NYC LL 144 (nyc-ll144), and Illinois AI Video (illinois-ai-video) full eval, continuous monitoring, and auditor-grade export packages are Enterprise. Run iris compliance scan or iris framework suggest to see what applies.

Free, open source, and built for real use.
Enterprise is coming as we build it in the open.

Community
Cedar policy engine
Compile plain-English intent to formally verified Cedar. Enforce before every LLM call.
Community
Policy compile & diff
GitOps policy workflow — intent in Git, Cedar compiled in CI, drift detected automatically.
Community
All LLM client integrations
Anthropic, OpenAI, Gemini, Vertex, LangChain — governed with the same Cedar engine.
Community
Enforcement-engine agnostic
Already running Cedar, Microsoft AGT, or another enforcement engine? IRIS adds the regulatory obligation mapping and evidence they don't provide — see Works with your stack.
Community
HITL (local)
Human-in-the-loop approval queue via CLI — pause, review, approve or reject high-risk actions.
Community
Evidence Vault (local)
Append-only JSONL event log by default; Evidence Vault v2 adds HMAC signing, hash chains, control mappings, retention lifecycle, and CI/CD evidence recording.
Community
CI/CD recording
GitHub Actions workflow and compliance checks in your pipeline.
Community
GitHub App (personal) — in development
PR comments with inline findings and one-line fix commands on your repos. Not yet published — use the GitHub Actions workflow today.
Community
MCP free tools
Connect IRIS to Claude Desktop and Cursor — scan, check compliance, list HITL reviews.
Community
Org policy validate
Validate .iris-security org policy files locally before merge.
Community
RBAC (basic)
Role-based access in the CLI and local SDK — viewer, engineer, admin roles.
Community
GDPR, HIPAA, EU AI Act assessment
Full offline rule eval, same engine as every other framework — iris compliance check --framework gdpr. EU AI Act currently ships 1 rule vs. GDPR's 8 and HIPAA's 9, with more on the roadmap. Certify export and continuous monitoring are Enterprise.

Building Enterprise capabilities in the open. Want in early? Reach out as a design partner.

Community
$0 — available now
Install free →

January 1, 2027 is closer than it looks.
Inventory your agents. Write the policy.
IRIS enforces the rest.

Open source. Five-minute install. Zero cloud required. Start building reasonable care now — not in December.