The fleet management industry needs to be able to predict when a truck or a van is about to break down. Not only does this prevent millions in lost revenues, it also has huge implications for supply chains. ‘Predictive maintenance’ is one of those spaces in which you will find several incumbent companies, such as BOSCH, and WABCO which offerer existing, “legacy” solutions.

In 2019 Stratio emerged from Portugal to tackle this issue with a combined hardware-under-thehood and AI approach to help OEMs, distributors and fleets. Its AI-based predictive fleet maintenance is designed to prevent things like public transportation delays or postponed/late arrival of deliveries.

It’s now raised a $12 million Series A funding round led by Forestay — the Deep Tech and SaaS Venture Capital arm of Waypoint Capital — with participation from existing investor Crane Venture Partners.

Stratio has so far secured several large transportation companies as customers, including Ford Trucks, Arriva, Keolis, RATP Dev, Go-Ahead, ComfortDelGro and claims its ARR has grown 2,700% since its Seed investment round.

Said Ricardo Margalho, CEO, commented: “Real-time predictive fleet maintenance provides a magnified look that leads to better planning and better decisions. That means higher quality and cheaper public transportation, on-time deliveries while serving more customers at a lower cost. Stratio’s technology is empowering fleet operators across the globe by providing them the most comprehensive and easy-to-manage platform in this space.”

Stratio’s technology also has an impact on the transition to zero-emissions for transportation companies because fully electric fleets require greater initial capital investment when compared to standard internal combustion vehicles, so transportation services must operate vehicles for longer and more intensively to make the initial outlay pay-back.

Frederic Wohlwend, Managing Partner at Forestay said: “Stratio’s technology fascinated us right from the beginning. Not only are they far advanced in terms of datasets uniqueness – which virtually allow them to work with any fleet across the globe – but they also have been growing at an incredible pace.”

Where Stratio says it has an edge over other players is that can deal with a great many different vehicle types, automakers’ brands, models etc.

Margalho told me: “We have spent 5 years researching and developing machine learning techniques – in the last two years alone 65% of our budget went directly to into R&D – for predictive maintenance while automating vehicle data interpretation. This means we can deploy our technology across all types of fleets while typically leveraging 10x times more parameters (data – temperatures, pressures, etc) from all the different components and systems.”

The result for customers is that the platform immediately becomes mission-critical, says Margalho: “This is the equivalent of X-rays in healthcare – you just can’t imagine going back to doing surgery without it. It’s a complete game-changer in this industry.”