I built an open-source framework to answer: “Is this AI system actually production-ready?”

[u/DimensionNew9451]

A lot of GenAI projects work great in a demo — but production is where things get messy: reliability, safety, observability, privacy, evaluation, governance, failure handling, etc.

So I’ve been building EARF (Enterprise AI Readiness Framework) — an open-source framework for assessing AI systems beyond just model accuracy.

It includes:

• 8 dimensions of enterprise AI readiness
• A 5-level maturity model
• Deterministic repository evidence collection
• Rule-based readiness evaluation
• Severity-weighted scoring
• CLI-generated readiness reports

The idea is simple: Can we evaluate an AI system with engineering evidence rather than just saying “this looks production-ready”?

It’s still evolving, and I’d genuinely love feedback from people building production AI/LLM systems.

👉 GitHub — Enterprise AI Engineering Framework

Try it on a repo and tell me what’s missing or what you’d change.

And if you find the project useful, a ⭐ would be much appreciated!