About This Session
Your RAG system works beautifully. Under GDPR, it has no legal basis to exist. Clean architecture. Proper embeddings. Maybe even agentic tool calling. You followed best practices. But when the auditor asks "what's the legal basis for this processing?" there's no answer. General-purpose "ask anything" chatbots have no defined purpose. Without a defined purpose, no legal basis can exist under GDPR. The architecture itself is the violation. In this talk, I'll live-code a "best practices" enterprise knowledge bot, then ask the questions nobody asks: Where is purpose limitation enforced? Where is legal basis documented? I'll show why anonymization doesn't save you. 97% accuracy isn't "anonymous" under GDPR. It's still PII. Then I'll show you the fix: a purpose-scoped bot architecture where legal basis is a first-class configuration item. Each bot gets a defined purpose, scoped data access, configured tools, and documented legal basis. The architecture enforces the boundaries. The retrieval layer can only access documents within that bot's scope. Non-compliance becomes architecturally impossible. The good news? You didn't waste your investment. This is a 50k governance layer, not a rewrite. Takeaways: - Why your RAG has no legal basis and how to fix it - The purpose-scoped bot pattern: document, enforce, and audit compliance by design - A brownfield rescue roadmap for existing systems
Topics
- AI Coding Assistants
- AI Standards
- Agentic AI
- Best Practices
- Documentation
- Generative AI (GenAI)
- Governance
- Next.js
- Node.js
- PostgreSQL
- Privacy
- React
- Software Architecture
- TypeScript
- Vector Databases
- Vibe Coding