Sales forecasting
Time-series models (ARIMA, LSTM) to anticipate demand and plan purchasing and staffing.
Predictive Analytics & Applied AI
Machine learning consulting and predictive analytics
BI tells you what happened; machine learning helps you anticipate what comes next. We build custom predictive models to forecast sales, set prices, detect anomalies or segment customers, and deliver them in a form your team can use, not as a technical report that ends up in a drawer.
PriceFrom €6,500 + VATAssessmentFree, 30 minutesModelsARIMA, LSTM, K-Means
Use cases01 02 03 04 05 06
What machine learning can do for you
Pricing and yield management
Predictive pricing analysis and dynamic pricing based on season and demand.
Anomaly detection
Alerts when a price, a cost or a sale falls outside the normal range, before it turns into a loss.
Customer segmentation
Customer or product groups built with K-Means or RFM to decide who to target and how.
Customer lifetime value
Predicting the value of each customer to focus your sales effort.
Built into your BI
Results appear in your dashboard, next to your other KPIs.
Pricing
Machine Learning, from €6,500 + VAT
Predictive Modelling and Machine Learning projects start from €6,500 + VAT. The final amount depends on the complexity and quality of the data. We start with the free 30-minute assessment to see what can be done with what you already have.
ExamplesDemoDeep Learning · LSTM DemoR · K-Means
Demo projects
Practical demonstration cases and data engineering prototypes applied to business.
Electric vehicle market in Spain
MAPE < 8 %Anomaly detection and 2025-2028 forecast.
Zara product segmentation
252 products3 clusters with pricing and inventory recommendations.
FAQ
Questions about machine learning
How much data do I need for a predictive model?
It depends on the case. For sales forecasting, two or three years of history helps capture seasonality; for customer segmentation, a solid customer and purchase history is enough. On the assessment call we review your data and tell you whether a model makes sense before any work starts.
What is the difference between BI and machine learning?
BI organises and visualises what has already happened: sales, margins, variances. Machine learning uses the same data to anticipate what may happen or to find patterns you cannot see at a glance. The usual path is to start with BI and add models once the data is clean.
What does the MAPE in your demos mean?
MAPE is the mean absolute percentage error of a forecast. A MAPE below 8 %, as in our electric vehicle demo, means the forecast is off by less than 8 % of the actual value on average. It is used to compare models and to know how far to trust them.
Do you work remotely?
Yes. We work 100 % remotely, and the whole service can be delivered in English: meetings, reports and documentation. We also work in Spanish and French, so teams spread across several countries can each use their own language. The initial 30-minute assessment is always a video call.
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