About

Making machine learning safe where math gets hard.

ZeroProofML began with a simple question: Why do models still fall apart on edge cases we can describe in math? We built a small, robust set of components that keep learning stable—even when divisions get tiny or functions blow up. Always‑defined math, safe normalization, and deterministic runs so you can train it safely and deploy with confidence.