Solutions / Data & artificial intelligence

Data that decides.
AI that acts.

Business intelligence, predictive analytics, data engineering, machine learning and applied AI. We turn scattered data into reliable decisions, and decisions into automatic actions — with judgment and human control.

Why data & AI

Data isn't worth having,
it's worth what it decides.

Most companies already have plenty of data; what they lack is turning it into clear, timely decisions. We start from the problem, not the hype: first reliable data and the dashboard, then prediction and, where it adds value, AI that acts. No smoke — with metrics and human oversight where it matters.

Orange light sparks rising in the dark
/ 01

Artificial intelligence

AI applied to your business: models, vision, language and automation with judgment — not AI for the hype.

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Three-dimensional data visualisation on a laptop screen
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Business intelligence & dashboards

Dashboards that turn your scattered data into clear, real-time decisions.

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Predictive analytics

We anticipate demand, churn, fraud or maintenance with models that predict, not guess.

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Orange light streams in motion, like flowing data
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Data engineering

The foundation of everything: pipelines, data warehouse and reliable data quality to build on.

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A three-dimensional structure of data and connected nodes
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Machine learning

Custom models trained on your data: classification, recommendation, forecasting and detection.

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AI assistants

Copilots and assistants that answer, search and draft over your knowledge, with human control.

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In one line

Data isn't worth having, it's worth the decisions it changes.

How we work

From scattered data
to an automatic decision.

01

Data & use case

We start from the problem and the data: which decision you want to improve and what information you actually have.

02

Proof of concept

We validate with a measurable pilot before investing at scale. If it does not deliver demonstrable value, we do not build it.

03

Production & integration

We take the model or dashboard to production, integrated into your systems and fed with up-to-date data.

04

Monitoring & improvement

We watch accuracy and drift, measure the real impact and retrain when needed.

Frequently asked questions

Do I need a lot of data to use AI?
Not always. It depends on the case: sometimes well-designed rules, a small amount of quality data or pre-trained models are enough. Other times you do need volume and history. Before proposing anything, we honestly assess whether your data can solve the problem and what is missing to get there.
What is the difference between business intelligence, predictive analytics and machine learning?
Business intelligence looks at the past and present: what happened and what is happening, in clear dashboards. Predictive analytics anticipates what is likely to happen (demand, churn, fraud). Machine learning learns patterns from your data to automate decisions and improve over time. They complement each other, and the path is often BI first, models later.
Is AI reliable? Doesn't it make things up?
Language models can be wrong if used poorly. That is why we ground answers in your data and sources, validate with metrics and keep human control over critical decisions. We measure accuracy before trusting a system, and design it to recognise when it does not know.
Is it secure and GDPR-compliant?
Yes. We work with encryption, least privilege and traceability, and we do not send sensitive data to third parties without control or a legal basis. We design in line with GDPR and, where possible, process data in your own environment or on European infrastructure.
How long does it take to see results?
We work in phases: a first measurable proof of concept is usually ready in weeks. From there we scale only what proves value, avoiding large investments before we have evidence.
Can I start with just a dashboard?
Yes, and it is often the most cost-effective move. The biggest leap is usually seeing your existing data clearly: a good dashboard reveals problems and opportunities that no AI can add if nobody looks at the numbers. From there, predictive analytics and machine learning follow naturally.

Which decision would you like to make with data?

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Want a real example? Read our CPPA X-RAY on 100 Montaditos, where we imagine how a connected system transforms operations.