Data Engineering & Intake
Ingest CSV, Parquet, JSON and Excel; validate schema, sizes and types; profile data and flag quality issues before any model runs.
Features
What the platform does today. Anything not shown here is not claimed.
Automated Feature Engineering
Type-aware transformations with entity- and time-aware splits so nothing leaks across train and test. Every transformation is recorded.
Model Orchestration
A versioned model zoo with gate-first selection: a candidate that fails a mandatory gate cannot win on a better average score.
Anomaly & Reliability
Statistical and industrial analytics (SPC, OEE, RUL, forecasting, anomaly scoring) for operational and financial signals.
Evidence-Grounded Insights
An assistant that answers from your computed results and cites them, and abstains when the data does not support a claim.
Audit & Governance
Dataset fingerprints, run parameters, seeds, metrics and artifact checksums, plus leakage, multicollinearity and performance gates.