EU AI Act Doc Generator — Automated Compliance Artifacts

Challenge

The EU AI Act (Regulation 2024/1689) requires AI system providers to produce extensive documentation: risk classification per Annex III, technical documentation per Annex IV (model cards, risk assessments, data governance records, human oversight procedures), and conformity assessment evidence. Manual documentation is time-consuming, inconsistent, and difficult to maintain over the 7-year retention period.

Build a platform that automates the generation of EU AI Act-compliant documentation artifacts.

Solution Architecture

Overview

┌─────────────────────────────────────────────────────────────────┐
│                    AI System Registry                            │
│         Model metadata · Training data · Deployment info        │
└───────────────────────────┬─────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────────┐
│                  Classifier Service                              │
│           Annex III risk level determination                    │
│      Prohibited · High-Risk · Limited · Minimal                 │
└───────────────────────────┬─────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────────┐
│                Doc Generator Service                             │
│                                                                  │
│   ┌─────────────┐  ┌─────────────┐  ┌─────────────┐            │
│   │ Model Card  │  │    Risk     │  │   Data      │            │
│   │  Generator  │  │ Assessment  │  │ Governance  │            │
│   └─────────────┘  └─────────────┘  └─────────────┘            │
│                                                                  │
│   ┌─────────────┐  ┌─────────────┐  ┌─────────────┐            │
│   │   Human     │  │ Conformity  │  │   Change    │            │
│   │  Oversight  │  │  Checklist  │  │    Log      │            │
│   └─────────────┘  └─────────────┘  └─────────────┘            │
└───────────────────────────┬─────────────────────────────────────┘
                            │
                            ▼
                 ┌──────────────────┐
                 │   S3 WORM Store  │
                 │  7-year retention │
                 └──────────────────┘

Risk Classification (Annex III)

Risk Level	Examples	Documentation Required
Prohibited	Social scoring, real-time biometric (public)	Cannot deploy in EU
High-Risk	Credit scoring, CV screening, medical diagnosis	Full Annex IV suite
Limited Risk	Chatbots, emotion recognition	Transparency notice
Minimal Risk	Spam filters, game AI	Voluntary best practices

Key Features

1. Annex III Risk Classifier

# Automated risk classification based on AI system characteristics
classification = classifier.evaluate(
    domain="employment",
    use_case="cv_screening",
    biometric_data=False,
    decision_impact="significant"
)
# Result: HIGH_RISK (Annex III, Category 4)

2. Annex IV Documentation Suite

Document	EU AI Act Reference	Auto-Generated
Model Card	Art. 11, Annex IV §1	Yes
Risk Assessment	Art. 9, Annex IV §2	Yes
Data Governance	Art. 10, Annex IV §3	Yes
Human Oversight	Art. 14, Annex IV §4	Yes
Accuracy Metrics	Art. 15, Annex IV §5	Yes
Conformity Checklist	Art. 43	Yes

3. Model Card Generator

# Model Card: CV Screening Assistant v2.1

## Model Details
- **Developer:** Acme Corp
- **Model Type:** Transformer-based classifier
- **Version:** 2.1.0
- **License:** Proprietary

## Intended Use
- **Primary Use:** Automated CV screening for job applications
- **Users:** HR departments, recruitment agencies
- **Out-of-Scope:** Final hiring decisions (human required)

## Training Data
- **Source:** Historical hiring decisions (2020-2024)
- **Size:** 1.2M CVs, 50K positive outcomes
- **Bias Mitigation:** Gender/age debiasing applied

## Performance Metrics
- **Accuracy:** 87% (test set)
- **False Positive Rate:** 8%
- **Fairness:** Demographic parity within 5%

## Limitations
- Performance degrades for non-English CVs
- Limited to structured job categories

4. Immutable Audit Trail

S3 WORM (Object Lock) for 7-year retention
Version history for all document changes
Cryptographic signatures (Sigstore cosign)
Export for notified body assessment

Tech Stack

Component	Technology	Purpose
API Service	FastAPI	REST API gateway
Classifier	Python + rule engine	Annex III risk classification
Doc Generator	Python + Jinja2	Artifact generation
Web UI	React 18 + TypeScript	Model registry + workflow
Database	PostgreSQL 14+	Model metadata, audit trail
Storage	S3-compatible WORM	Artifact retention (7 years)
Secrets	HashiCorp Vault	API keys, credentials

Compliance Coverage

EU AI Act Article	Requirement	Platform Feature
Art. 9	Risk management system	Risk assessment generator
Art. 10	Data governance	Data governance doc generator
Art. 11	Technical documentation	Full Annex IV suite
Art. 12	Record-keeping	Immutable audit trail (7 years)
Art. 13	Transparency	Model card generator
Art. 14	Human oversight	Oversight procedure doc
Art. 15	Accuracy, robustness	Performance metrics doc
Art. 43	Conformity assessment	Conformity checklist

Results & Metrics

Target Market

AI system providers deploying in EU
High-risk system operators (Annex III)
Notified bodies performing conformity assessments

Revenue Target

$200K Year 1 (SaaS + enterprise licenses)
Per-model or organization-wide pricing

Architecture Decisions

Template-based generation: Jinja2 templates for consistent, auditable output
S3 WORM over database: Meets 7-year immutability requirement
Sigstore keyless signing: Tamper-evident without key management burden
React wizard UI: Guided input reduces user errors
Version pinning: Each artifact version is immutable once generated