SchemaPilot

SchemaPilot is a web app (AI app + traditional app) that turns messy, real-world business tables into deployable models with minimal ML expertise. Users connect a warehouse or upload CSVs, and SchemaPilot automatically profiles columns, detects joins, fixes common data issues (leaky features, time leakage, duplicates), and builds baseline models with transparent feature lineage. The core focus is tabular prediction for operations: churn, demand, lead scoring, fraud flags, and ticket routing. It generates a “data contract” report showing required fields, acceptable ranges, drift monitors, and retraining triggers so models don’t silently rot. Outputs include a hosted inference API, batch scoring jobs, and a human-readable model card with cost/latency estimates. It’s realistic: it won’t beat custom ML teams on every dataset, but it will reliably get teams from zero to a usable baseline and keep it from breaking.