MathFi.ai Information

At MathfFi.ai we invented a new Machine Learning architecture. It finds the rare, costly events that standard models miss. MathFi.ai is a hosted prediction service that turns your own noisy and raw labelled-tabular data into deterministic, production-ready predictive decisions in a single day. We turn a production prediction into something you call, not something you staff. GenAI taught machines to talk; the next decade is teaching machines and agents to decide. MathFi.ai is the deterministic layer the agents call when a decision must be right, repeatable and auditable. The answers that improve a business are already in its data: which customer will churn, which claim is fraud, which patient needs attention. Seeing them normally takes a scarce data-science team and a quarter or more per model, so most of that value is left on the table. MathFi.ai releases it. Bring labelled data, call an API, and we refine, build, host and serve a production model the same day. At the core is Cellular Balanced Learning (CBL) ©, a proprietary, deterministic ML architecture (not a wrapper around open-source models). It automates data prep and feature selection, replaces 100+ hyperparameters with just two, and gives rare events their own structure instead of overfitting them. Models train in minutes and return the same prediction for the same input, every time — auditable by regulators, explainable to analysts, and trustworthy enough for autonomous agents to call and replay. Two products run on CBL: Feature Refinery © cleans a raw, noisy feature set and selects what matters; Model Crucible © builds and serves the production model, live today via a public REST API and Python SDK. In independent May 2026 benchmarks across credit, clinical, insurance-fraud and industrial datasets, MathFi.ai led the five most-used methods on F1, precision and recall for the rare class, where the money and risk concentrate. Now onboarding beta and pilot customers. Register your interest at mathfi.ai.