Your AI is only as good as the data underneath it — and most companies can’t even say where their data lives. Stefan Opitz, founder of Codoflow (Code of Flow GmbH), explains a bottom-up approach to data architecture that makes SMEs AI-ready in weeks, not years, with real-time collaboration and software-style change management.
Full article, links, and transcript:
Read the full episode notes on Startuprad.io
Why this episode matters: Every AI initiative quietly depends on trustworthy data architecture, yet it’s the layer most startups ignore until it breaks. This is a practical map for getting your data house in order before you train a model on it.
In this episode, we cover:
Related episode: From GenAI Prototype to Production: MCP & AI Agents.
Chapters
00:00 – Meet Stefan Opitz and Codoflow
04:38 – Why companies lose track of their own data
07:26 – Bottom-up vs. top-down data architecture
11:07 – Tools aren’t enough: methodology and ownership
14:44 – Why AI needs clean, transparent data
18:54 – Making data design accessible for SMEs
21:21 – Versioning and pull-request-style change management
25:42 – Real-time collaborative data modeling
33:14 – The UX challenge: simple for IT and business users
39:21 – Coordinating multi-system data releases
42:24 – Founder lesson: solve complexity simply
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