Out of stealth, Stratio emerges with predictive AI to stop your bus breaking down

Remember that future we were promised where our vehicle magically tells us that we’re about to break down? Or actually never does? Or that the pick-up truck arrives before the driver even knows something wrong? That future is arriving. But like many things, the practical reality is that this technology starts to arrive in the fleet management industry before it arrives for consumers.

The market for maintenance of fleets of buses and trucks is worth $200B in annual expenditure, so as you can imagine, it’s a juicy sector to get into. Down in Portugal, a tea of entrepreneurs and scientists assembled to look into this and came up with a fascinating startup that is now attracting the attention of investors.

Today, Stratio is emerging from stealth to help OEMs, Distributors and Fleets benefit from AI-driven predictive intelligence.

The idea is to apply machine learning models that retrieve and analyze millions of data points per vehicle per day to vehicles both in development and on the road. It turns out that if you compare the real vs. the expected behaviour of the actual vehicle components themselves, you can improve automated testing and predictive intelligence that can assess the vehicle’s condition. Then you can detect early anomalies and failure. This is exactly what Stratio does.

It does this by putting a sensor box-of-tricks under a vehicle, like a bus. This box connects with existing sensors in the vehicle using the existing API – something crucial for OEMs. Using proprietary machine learning it can predict when something will break, days ahead of time. Most existing boxes like this only track location, not analytics.

Stratio also works with OEMs during the vehicle testing phase to identify issues and their root cause to get more reliable vehicles to market faster, lower the potential for warranty claim fraud costs and expand the aftersales revenues. It’s a triple whammy in cost savings.

Stratio has now attracted a $3.5m VC round from London-based Crane VC, with participation from fellow London VC, Localglobe.

The round is one of the largest ever seed deals in Portugal and potentially the largest enterprise/deep tech first investment in the country.

It has a proprietary AI engine, Stratio CortexTM, and technology support from the European Space Agency. Ultimately the aim is to apply machine learning models and enable the so-called “zero downtime” future.

Rui Sales and Ricardo Margalho, co-founders of Stratio say the idea for Stratio came to them when their bus broke down and they missed what could have been a career-changing meeting in New York: “Knowing that today’s existing vehicles produce a massive amount of data, we set out to build a machine learning product suite that analyses high-density vehicle data in real time to predict and prevent vehicles from breaking down.”

Stratio launched in 2017, after receiving technological support from the European Space Agency and earning recognition from the EU Commission.

Alongside the co-founders is Rune Prytz, a former Volvo Trucks Research Engineer in machine learning and big data, who now leads all of Stratio’s efforts in AI. Stratio now counts MAN, DAF Trucks and VECTIA as customers, among others.

Krishna Visvanathan, Partner at Crane Venture Partners, commented “Stratio Automotive is one of the most exciting companies in our portfolio of data-driven enterprise software businesses. It has the trifecta of a super product, a deep data moat coupled with AI expertise and great customer traction.”

So far, Stratio has attracted customers and operations in over 10 key markets
across Europe, the UK, US, India and Singapore.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s