01 Causal AI, built on Digital Brain models
A proprietary causal AI engine built on digital brain models from 20 years of EPFL neuroscience research. It learns the real drivers behind your numbers from historical actuals plus external signals like macro indicators, pricing, promotional calendars, and CRM exports. Self-adapts as conditions shift with automatic drift detection and refit, so accuracy holds.
02 Speed without a data-science queue
Run a full backtest or forecast from CSV or Excel input. Automated model selection, ensembling, hyperparameter tuning, calibration, and validation all happen under the hood, so anyone who can operate a spreadsheet can produce a production-grade forecast in hours.
03 Explainability for forecast reviews
Digital brains are interpretable by design. Each run returns confidence bands, automated driver analysis, and a head-to-head benchmark against pretrained models like Chronos-2, ready for leadership review.
04 Hierarchical coherence
Forecasts roll up coherently from representative, product, and region levels to global totals. Top-down and bottom-up always agree, so Finance and Sales work from one shared number instead of parallel shadow forecasts.