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Predict your company's future with your data.

From descriptive analytics to automated decisions. We integrate artificial intelligence to turn your most complex challenges into growth opportunities.

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How AI amplifies your data capital

Augmented Analytics

Detect warning signals — anomalous behaviors, emerging risks — that manual audits cannot isolate at scale.

Custom Predictive Models

Attrition, demand forecasting, customer scoring: we build models aligned to your context and integrated into your data roadmap.

Operational Deployment

Your models don't stay in a Notebook. We integrate them directly into your workflows for real-time decision making.

Simulated data for illustrative purposes

Case Study: Demand Forecasting (Distribution)

A multi-category distributor was running procurement on rolling averages — a method unable to capture seasonal peaks or promotional lifts. By training a forecasting model on 24 months of sales history, we replaced intuition with a 30-day forecast, tested across all product families.

−23%

fewer stockouts

30 days

of lead time visibility

more accurate than trend-based methods

Demand Forecast

Actual vs model forecast over 12 months, with a 30-day horizon for the next 3 months. The forecast (orange line) tracks seasonal patterns that classical methods smooth over.
Actual vs model forecast over 12 months, with a 30-day horizon for the next 3 months. The forecast (orange line) tracks seasonal patterns that classical methods smooth over.

Accuracy by Product Family

Forecast error (MAPE) by product family, naive rolling average vs ML model. Lower is better.
Forecast error (MAPE) by product family, naive rolling average vs ML model. Lower is better.

What this model reveals

  • The model captures promotional peaks and seasonal effects that rolling averages smooth out — the most volatile families (Fashion, Sports) gain up to 15 percentage points of accuracy.
  • A 30-day horizon lets buyers place orders within real supplier lead times — a constraint systematically ignored in classical planning approaches.
  • Over the first 3 months of deployment, stockouts dropped by 23% with no increase in inventory levels — better forecasting frees up capital, not just accuracy.

Your next growth lever is already in your data.

Let's talk about what AI can do for your business — concretely and without jargon.

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