Unused data
Years of sales, customers and purchases in the ERP and CRM that nobody turns into forecasts.
AI and machine learning for business
Stay ahead of your customers, your sales and your cash.
We apply machine learning and AI to the data you already have in your ERP, your CRM, your point of sale or your spreadsheets. Every prediction comes with its reasons and lands in your day-to-day work: Power BI dashboards, alerts or assistants.
- Weeks, not yearsto the first use case in production
- Explainable modelsevery prediction, with its factors
- Your data stays homeon your infrastructure or in Spain
- In your daily workPower BI, alerts and assistants
01Why
Deciding by looking in the rear-view mirror is expensive.
Most companies already have the data to get ahead. What is missing is turning it into forecasts the business trusts.
Late decisions
You find out when the customer has already left, the stock has run out or the month has closed.
Spreadsheets that do not scale
Manual forecasts that take hours every month and depend on a single person.
Black boxes
Models nobody understands, which is why the business ends up not using them.
02What we solve
Six business areas, one way of working.
Sales and revenue
- Sales forecasts by product, store or channel.
- Revenue and month-end forecasts.
- The effect of promotions, weather and the calendar.
- What-if simulations for the leadership team.
Customers
- B2B and consumer churn.
- Segmentation by value and purchasing behaviour.
- Win-back campaigns prepared with AI.
- Review and satisfaction analysis.
Purchasing and inventory
- Demand and consumption forecasts per item.
- Safety stock and reorder points.
- Purchase recommendations with human approval.
- Cash freed up without stock-outs.
Finance
- Income and cash forecasts.
- Results from several sites in one dashboard.
- Margins and profitability.
- Risk and fraud with explainable models.
People and service
- Occupancy and demand forecasting.
- Absenteeism and shift planning.
- Service and resolution times.
- Team workload.
Leadership
- Power BI dashboards.
- Mobile alerts when something drifts.
- Questions to your data in natural language and by voice.
- Ready-to-use forecasts with Profeeta.
03In motion
This is what a forecast that reacts to context looks like.
Revenue forecasting
Normal month
HistoryForecastConfidence
- Forecast close
- €3.02M
- Versus baseline
- +0.0%
- Weather+0.0%
- Promotions+0.0%
- Holidays−1.2%
Inventory optimisation
Inventory worth €2.50M
Working capital you could free up
€300k – €500k
€120k to €200k per million of inventory, with OTIF 1.5 points higher and stock-outs anticipated weeks ahead.
Explanatory animations with illustrative values.
04How
From data to decision, in four steps.
- 01
The business question
Which decision you want to improve and which metric will measure the result.
- 02
Your data
ERP, CRM, point of sale or spreadsheets, organised and enriched with external factors such as weather or the calendar.
- 03
A model that explains itself
Every prediction comes with the factors that drive it, so the business can trust it.
- 04
In your daily work
Dashboards, alerts or an assistant, with the result tracked against the metric.
05Cases
What we have already solved, told by its why.
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Contact
Let’s talk.
Tell us about your challenge by email or phone. In a first, no-strings session we align scope and approach, and tell you honestly whether we can help.
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