Next-gen predictive AI for enterprise forecasting
If LLMs help companies work with language, ExcellerIA helps companies forecast the numbers that run the business - demand, sales, staffing, capacity, and risk - using predictive AI pretrained for enterprise forecasting.
Built on a wide range of real-world forecasting patterns and continuously improved through deployments - with strict data separation and only with the permissions defined in your agreement.
Real results, real scale
For Intermarché Drive, France's leading online grocery click-and-collect channel, forecast accuracy improved from ~80% to 93% on customer visits and orders.
The limits of today's forecasting
Most companies still rely on semi-manual forecasting pipelines. As complexity and data volumes grow, forecasts stay fragile. They don't survive real life: promotions, weather, local events, channel shifts.
Imprecise
Accuracy collapses as soon as you mix promotions, seasonality, local events, weather and channel shifts.
Manual and fragile
Forecasts are stitched together in spreadsheets and ad-hoc models, not produced by a robust engine that can run every day in production.
Under-using data
Large internal datasets — CRM, web, loyalty, operational logs, sensors — stay dormant because existing tools cannot ingest and exploit them at scale.
The ExcellerIA engine
ExcellerIA turns forecasting from a manual, fragile process into an AI engine that runs in production.
We plug into your existing data
CRM, web analytics, loyalty programs, POS, sensors, weather, local events — no data overhaul required.
Learn your operational patterns
The engine explores 4M+ scenarios automatically, pre-trained on real business cases across retail, mobility and industry.
Deliver ready-to-use forecasts
Staffing, inventory, capacity, slots — predictions that feed your decisions, not just your dashboards.
Engine Features
01
Built for messy, real-life data
Handles promotions, seasonality, local events, weather and channel shifts — the things that usually break traditional pipelines.
02
Industrial, not artisanal
Automated pipelines and APIs instead of spreadsheets and one-off models — designed to run in production, not just in slides or notebooks.
03
Data-hungry by design
Ingests and exploits large internal datasets — CRM, web, loyalty, operational logs, sensors — at scale.
04
Pre-trained on real business use cases
Already trained and stress-tested on live scenarios: online grocery, logistics, mobility and parking. Shortens time-to-value for new clients.
Case study – Intermarché online store
Anticipating customer visits and orders at store level, under real operational constraints.
Intermarché Drive France's leading online grocery click-and-collect channel
Accuracy Improvement
Scenarios Explored
Stores
Nationwide
Retail
Sales, shopping carts, traffic, online grocery and click-and-collect flows.
Mobility and parking
Mobility demand, parking occupancy, multimodal flows.
Industry and logistics
Production, capacity, inventory and logistics flows.
We plug into existing data sources, leverage our pre-trained engine and adapt to each client's constraints, with fast deployment to production.
Predictive analytics market by 2028
Operational forecasting — our wedge
