AI framework: open source, reliable, scalable & customizable
Datapizza AI Framework gives engineers full control to create trustworthy GenAI—without unnecessary complexity. Built for engineers who need flexibility and transparency, it fits your stack and lets you customize every layer, from model choice to deployment.
Hey PH 👋 After a year shipping RAG systems and AI agents for real customers, we kept hitting the same wall: heavy abstractions made debugging painful, slowed onboarding, and hid the parts we needed to control. We didn’t want another “magic” layer—we wanted a thin, modular framework that stays close to provider SDKs and lets engineers intervene at any depth. So we focussed on: - Low abstraction , full control: no black boxes; every step is observable (tracing, structured logs, clear error handlin
Love the thin, modular approach. Tracing, structured logs, clear error handling, and swap-anything modules are exactly what production teams need. Open source, provider agnostic, close to SDKs, and already battle tested. Excited to try it on our next RAG. Congrats!
Hi Product Hunt, I am kinda excited to finally launch our framework. When I joined Datapizza, we found most existing implementation too black boxes, we wanted to build something from scratch and our customization, like, our R&D experimentation were just sitting in scripts with no clear path to production. Thus we created something fully modular, but only with the abstraction that were truly needed to keep it as lightweight as we could. Like, bridging the gap between research and production-r
Feels great to finally share what we’ve been working on. We started building Datapizza AI because the existing tools we used never felt quite right: too many layers, too little control, and no real way to reuse what our R&D team kept discovering (customization). We wanted a framework that stays close to the SDKs, fully modular and transparent/observable, where every component — from RAG to agents and evaluation — can evolve an be highly customized in real world use cases. Turning months of r
It feels amazing to finally open source something we’ve been building and refining for over a year. What’s even better is seeing the community already extending it, adapting it to their needs, and using it in their companies to build GenAI solutions that are truly production-ready. Our goal has always been simple: make GenAI create real impact for people and organizations. Seeing what's happening out there makes me feel we’re on the right track 🔥
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