Artificial Intelligence
What we know how to do, not just what we sell.
Nine capabilities, one method: models chosen for the problem, data handled where it belongs, systems that actually reach production — on GPUs, in the cloud or inside a microcontroller.
The capabilities
The proof
A model, in your browser
Demand forecasting computed locally, right now, on synthetic data: trend, weekly seasonality, a confidence interval that widens with the horizon and an error measured on a real backtest. A didactic taste: GA.IA does this with ensemble models, on your data.
GA.IA does it on real data →The method
From the problem to the system in production
- 01
Scoping
A 30–60 minute call: goal, available data, constraints (privacy, latency, hardware) and success KPIs.
- 02
Measured prototype
A proof of concept in 4–6 weeks with real metrics — accuracy, latency, cost per inference — before investing in the full system.
- 03
Production
Integration with existing systems (PLC, ERP, MES, CRM), monitoring, governance and EU AI Act compliance; then ongoing support.
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