Architecture Decision Record (ADR) - EU AI Act Compliance Bot

Date: 2026-02-04
Status: Active
Project: EU AI Act Compliance Bot - Automated Regulatory Assessment
Author: Oksana Siniaieva (via Autonomous Agent)

Context

The EU AI Act enforcement begins in 2026, creating a massive compliance market for European companies. Organizations need automated tools to assess their AI systems against EU AI Act requirements and receive actionable compliance recommendations.

Market Opportunity:

• EU AI Act enforcement deadline: 2026
• Millions of EU businesses need compliance assessment
• Complex regulatory framework requiring expert interpretation
• Limited specialized compliance tools in market

Decision

Build an autonomous AI compliance assessment bot that:

1. Analyzes AI system descriptions and architectures
2. Maps them against EU AI Act requirements
3. Provides detailed compliance recommendations
4. Generates compliance reports and action plans

Architecture Overview

System Components

┌─────────────────────┐    ┌─────────────────────┐    ┌─────────────────────┐
│   Web Interface     │    │  Analysis Engine    │    │  Knowledge Base     │
│  - Input Forms      │◄──►│  - Risk Assessment  │◄──►│  - EU AI Act Text   │
│  - Report Display   │    │  - Compliance Map   │    │  - Risk Categories  │
│  - Export Tools     │    │  - Recommendations  │    │  - Requirements DB  │
└─────────────────────┘    └─────────────────────┘    └─────────────────────┘
           │                          │                          │
           ▼                          ▼                          ▼
┌─────────────────────┐    ┌─────────────────────┐    ┌─────────────────────┐
│   API Gateway       │    │   Claude LLM        │    │   Vector Database   │
│  - Authentication   │    │  - Analysis Logic   │    │  - Semantic Search  │
│  - Rate Limiting    │    │  - Report Gen       │    │  - Regulation Index │
└─────────────────────┘    └─────────────────────┘    └─────────────────────┘

Technology Stack

Backend

• Framework: FastAPI (Python)
  • Rationale: Fast development, excellent async support, auto OpenAPI docs
• LLM Integration: Anthropic Claude API
  • Rationale: Superior reasoning for complex regulatory analysis
• Vector Database: Pinecone or Chroma
  • Rationale: Efficient semantic search through regulation text
• Knowledge Base: SQLite → PostgreSQL migration path
  • Rationale: Simple start, scalable evolution

Frontend

• Framework: Next.js 14 (React + TypeScript)
  • Rationale: SSR/SSG for SEO, excellent DX, mature ecosystem
• UI Library: Tailwind CSS + shadcn/ui
  • Rationale: Rapid development, consistent design system
• Charts/Visualization: Recharts
  • Rationale: React-native charts for compliance dashboards

Infrastructure

• Hosting: Vercel (Frontend) + Railway/Fly.io (Backend)
  • Rationale: Simple deployment, good free tiers for MVP
• Database: Supabase (PostgreSQL + Auth)
  • Rationale: Integrated auth, real-time features, generous free tier
• Monitoring: Sentry + PostHog
  • Rationale: Error tracking + analytics for product insights

Implementation Phases

Phase 1: Foundation (Week 1-2)

Goal: Basic analysis engine with core EU AI Act knowledge

Deliverables:

• EU AI Act knowledge base ingestion
• Basic AI system analysis prompt engineering
• Risk categorization logic (Unacceptable, High, Limited, Minimal)
• Simple CLI tool for testing

Sub-tasks:

1. Research and compile EU AI Act requirements
2. Create structured knowledge base schema
3. Implement document embedding and vector search
4. Design analysis prompts for Claude
5. Build CLI tool for testing analysis logic
6. Create unit tests for core analysis functions

Phase 2: Web Interface (Week 3-4)

Goal: User-friendly web application for compliance assessment

Deliverables:

• Responsive web interface
• AI system input forms
• Compliance analysis dashboard
• PDF report generation

Sub-tasks:

1. Set up Next.js project with TypeScript
2. Design and implement input forms for AI system descriptions
3. Create compliance dashboard with visualizations
4. Build PDF report generation with compliance recommendations
5. Implement responsive design for mobile/desktop
6. Add error handling and loading states

Phase 3: Advanced Features (Week 5-6)

Goal: Enhanced analysis and user experience

Deliverables:

• Multi-language support (EN, DE, FR, ES, IT)
• Compliance timeline and roadmap generation
• Integration with common AI development frameworks
• Advanced reporting and analytics

Sub-tasks:

1. Implement i18n for major EU languages
2. Build compliance roadmap generator
3. Create API integrations for popular AI frameworks
4. Add advanced analytics and compliance tracking
5. Implement user authentication and project management
6. Build admin dashboard for system monitoring

Phase 4: Market Launch (Week 7-8)

Goal: Production-ready application with go-to-market strategy

Deliverables:

• Production infrastructure
• Documentation and user guides
• Marketing website
• Freemium business model implementation

Sub-tasks:

1. Deploy to production infrastructure
2. Create comprehensive user documentation
3. Build marketing landing page
4. Implement freemium pricing model
5. Set up analytics and monitoring
6. Launch beta program with selected users

Risk Assessment and Mitigation

Technical Risks

1. LLM Hallucination in Legal Context
   • Mitigation: Extensive prompt testing, human review layer, citation requirements
2. Regulation Interpretation Accuracy
   • Mitigation: Legal expert consultation, continuous knowledge base updates
3. Scalability Under Load
   • Mitigation: Async processing, caching layer, horizontal scaling design

Business Risks

1. Regulatory Changes
   • Mitigation: Automated monitoring of regulation updates
2. Competition from Legal Tech Giants
   • Mitigation: Focus on AI-specific niche, superior UX, faster iteration
3. Liability Concerns
   • Mitigation: Clear disclaimers, "advisory only" positioning, insurance

Success Metrics

Technical KPIs

• Analysis accuracy: >90% (validated against legal expert reviews)
• Response time: <30 seconds for standard assessment
• Uptime: >99.5%
• User satisfaction: >4.5/5

Business KPIs

• User signups: 1000+ in first 3 months
• Paid conversions: 15% conversion rate
• Revenue: €10k MRR by month 6
• Market presence: Featured in 3+ EU AI compliance articles

Future Enhancements

1. API Integration Marketplace

   • Direct integrations with major AI platforms (OpenAI, Anthropic, AWS, etc.)
   • Automated compliance monitoring for deployed models

2. Compliance Automation

   • CI/CD integration for continuous compliance checking
   • Slack/Teams notifications for compliance updates

3. Advisory Services

   • Expert consultation marketplace
   • Custom compliance strategy development

4. Industry Specialization

   • Healthcare AI compliance modules
   • Financial services AI regulations
   • Automotive AI system assessments

Development Approach

Iterative Development

• Weekly sprints with Friday demos
• Continuous user feedback integration
• Minimum viable product (MVP) first, iterate based on real usage

Quality Assurance

• Test-driven development for core logic
• End-to-end testing for user workflows
• Legal expert review of compliance logic

Documentation

• Comprehensive API documentation
• User guides and video tutorials
• Developer documentation for extensibility

---

Next Steps:

1. Set up development environment
2. Create GitHub repository
3. Begin Phase 1 implementation
4. Update Notion with progress tracking

Repository: https://github.com/Ksushik/eu-ai-act-bot (to be created)