Why Compliance in AI-Assisted Development

The use of AI agents in software development introduces specific regulatory risks:

• Traceability: Who wrote each line of code? A human or an AI?
• Governance: How are AI agents configured and controlled?
• Transparency: Is the use of AI properly documented?
• Security: Are there guardrails to prevent undesired behavior?
• Accountability: Is there human review before deploying AI-generated code?

licit evaluates these aspects against established regulatory frameworks.

EU AI Act (Regulation EU 2024/1689)

Scope

The EU AI Act is the first comprehensive regulatory framework for artificial intelligence. It entered into force in August 2024, with gradual enforcement until August 2027.

licit evaluates the articles relevant to development teams using AI agents:

Evaluated Articles

FRIA — Fundamental Rights Impact Assessment

The FRIA (Fundamental Rights Impact Assessment) is mandatory for high-risk AI systems under Art. 27. licit generates an interactive FRIA in 5 steps:

1. System description: What it does, what it is used for, who the users are.
2. Identification of affected rights: Which fundamental rights could be impacted.
3. Risk assessment: Probability and impact of each risk.
4. Mitigation measures: What controls are implemented.
5. Conclusions and recommendations: Final assessment.

Command:

licit fria

Annex IV — Technical Documentation

Annex IV defines the technical documentation required for AI systems. licit generates this documentation by auto-populating it from:

• Project metadata (pyproject.toml, package.json)
• CI/CD configuration
• AI agent configurations
• Testing frameworks
• Security tools

Command:

licit annex-iv --organization "My Company" --product "My Product"

OWASP Agentic Top 10

Scope

The OWASP Agentic Top 10 identifies the 10 main security risks in applications that use AI agents. licit evaluates the project’s posture against each risk.

Evaluated Risks

Mapping to Evidence

Each OWASP risk maps to collectible evidence:

ASI-01 (Excessive Agency)
  ├── has_guardrails → Are guardrails configured?
  ├── guardrail_count → How many controls exist?
  └── has_human_review_gate → Is there human review?

ASI-02 (Uncontrolled Autonomy)
  ├── has_budget_limits → Are there budget limits?
  ├── has_dry_run → Does dry-run mode exist?
  └── has_rollback → Is there rollback capability?

ASI-06 (Insufficient Monitoring)
  ├── has_audit_trail → Is there an audit trail?
  ├── audit_entry_count → How many entries?
  └── has_otel → Is there OpenTelemetry instrumentation?

How licit Evaluates Compliance

Evaluation Process

1. Detect     → ProjectDetector analyzes the project
2. Collect    → EvidenceCollector gathers evidence
3. Evaluate   → Evaluators apply framework requirements
4. Classify   → Each requirement: compliant / partial / non-compliant / n/a
5. Report     → Report with evidence, gaps, and recommendations

Evidence Sources

Provenance evidence (licit trace) directly feeds the transparency articles (Art. 13) and traceability (Art. 10) of the EU AI Act, as well as the monitoring controls (ASI-06, ASI-10) of the OWASP Agentic Top 10.

Compliance Levels

Compliance Reports

Available Formats

Report Structure

# Compliance Report — My Project
Generated: 2026-03-10

## Summary
- EU AI Act: 72% compliant (13/18 controls)
- OWASP Agentic: 60% compliant (6/10 controls)

## EU AI Act
### Article 9 — Risk Management
Status: PARTIAL
Evidence: FRIA exists but incomplete
Recommendation: Complete FRIA sections 3-5

### Article 14 — Human Oversight
Status: COMPLIANT
Evidence: GitHub Actions requires approval for deployment
...

## Gaps
| Priority | Requirement | Gap | Effort |
|---|---|---|---|
| 1 | ART-9-1 | No risk assessment | Medium |
| 2 | ASI-01 | No guardrails | Low |

CI/CD Gate

licit can act as a compliance gate in CI/CD pipelines:

# .github/workflows/compliance.yml
name: Compliance Check
on: [push, pull_request]

jobs:
  compliance:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0   # Required for git analysis

      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"

      - name: Install licit
        run: pip install licit-ai-cli

      - name: Run compliance check
        run: licit verify
        # Exit 0 = pass, Exit 1 = fail, Exit 2 = warnings

Exit codes:

Future Frameworks (V1+)

licit is designed to support additional frameworks:

The frameworks/ architecture allows adding new frameworks by implementing an evaluator with the corresponding Protocol interface.