Empower planners, sales, marketing, and production with an AI-first demand engine. Our deep learning framework combines internal, external, and historical data to continuously improve the accuracy of every forecast and S&OP decision.
From data ingestion to collaborative S&OP, the engine is built as a platform and framework that can be reused across products, channels, and countries.
Simulate the future before it happens. Planners can create private scenarios to test strategies without affecting the live plan, then promote the best scenario to the official forecast.
Don't let one-time events ruin your forecast history. The AI automatically detects spikes (e.g., COVID panic buying, channel stuffing) and suggests corrections before feeding data into deep learning models.
AI PLATFORM & FRAMEWORK
We use advanced AI and deep learning with internal, external, and historical data, then wrap it with a collaboration layer for Sales, Marketing, and Production to adjust, approve, and continuously improve the accuracy of the consolidated plan.
Combine every data source that impacts demand: internal data, external data, and historical patterns into a central feature store that can be reused across AI and deep learning models.
Internal
External
Historical
The engine can run multiple model families in parallel (Prophet, XGBoost, LSTM, Transformer) and automatically pick the best model per product-family and horizon.
Use Deep Learning (e.g., LSTM, Transformer) together with traditional models to uncover hidden patterns such as cross-product cannibalization, multi-channel impact, and long-term trends that are invisible to the human eye.
Not just a forecast report, but a collaboration workspace where every team can see the AI baseline, make adjustments based on their own insights, and lock a consensus plan with full traceability.
A Champion–Challenger pipeline runs new models in the background and promotes only those that show real accuracy improvements on production data.
The system doesn’t stop at a one-time model implementation. It has a feedback loop that continually brings actual vs. plan back to retrain the model and monitors MAPE, bias, and stability across categories and regions.
Designed as a platform and framework that can be reused across multiple projects – integrating with SAP, TMS, WMS, BI, and the data lake via an API-first architecture, and ready to expand into other regions in the future.
Schedule a personalized demo using your own historical, internal, and external data. We'll show you how our AI demand platform – plus S&OP collaboration – can lift accuracy and reduce firefighting across your network.