How does predictive AI help start-ups grow?

Between budget uncertainties, inventory management and customer loyalty, start-ups often lack the tools to anticipate the future. Predictive AI provides a clear and measurable answer to these challenges. 

Co-founder and CTO of Excelleria, Jean-Louis Decosse explains why this technology is becoming an essential asset for start-ups and major corporations alike.

Hello Jean-Louis. Where does your passion for artificial intelligence come from?

My career has been in IT and software, both in start-ups and in large corporations. I started out in big data, then turned to AI.

I'm convinced that, properly employed, AI solutions will deliver extremely useful and effective services to businesses.

You founded Excelleria in 2023. What is your mission?

Today, there are three main branches of artificial intelligence. 

The first is the type of AI known to the general public: generative AI, capable of producing texts, reports, images and illustrations. The second is predictive AI, which relies on historical data and algorithms to anticipate the future. The third is prescriptive AI, which recommends actions based on predictions. 

Excelleria focuses on predictive analysis. We collect our customer's historical data, and thanks to our Axolot engine, we can make personalized predictions. 

Our customers range from small structures to large groups, as all companies have an interest in this type of analysis: inventory management, customer churn, budget projections, footfall or visit rates.

Many companies still doubt the ROI of AI. What does predictive AI offer in concrete terms?

Let me give you a concrete example. One of our customers is a major retailer with several sites. Before Excelleria, they used Excel to make their forecasts, copying past data and adding a percentage trend. As a result, their predictions turned out to be correct to within just 20%, which is far from enough to effectively manage their business. 

With Excelleria, we trained a global model, which was then applied to each of their sites, to achieve a better level of precision and accuracy of around 97%. That's the power of predictive AI: transforming raw data into actionable insights that deliver real business value.

Predictive AI can also be useful for younger companies, especially start-ups. Can you tell us more?

A start-up has to deal with a lot of uncertainties: the relevance of its business model, financial management, anticipating customer needs. Predictive AI gives them a forward-looking vision, a bit like a "crystal ball", but based on real data.

The most accessible use cases for a start-up are :

• sales forecasts,
  
• reducing customer churn,
  
• dynamic pricing,
  
• supply chain and inventory management.

We support our customers right from the start, studying their needs, selecting and enriching data (e.g. weather, economic context), then setting up appropriate predictive models.

How do you see predictive AI evolving in 3 to 5 years' time?

I'm convinced that all the classic management rules - order support, industrial MRP, churn forecasting, budget management - will be replaced by AI algorithms.

In fact, in a few years' time, we won't even be talking about AI anymore, as it will be fully integrated into corporate systems.

At Excelleria, our mission is to carry the banner of predictive analytics and make it accessible to all businesses, large and small.