Viaduct, a machine learning startup that allows original equipment manufacturers (OEMs) to glean insights from their connected vehicle data, announced that it has raised $11 million in Series A funding, led by Innovation Endeavors and joined by Exor Seeds and Box Group.
Based in Menlo Park, California, Viaduct gives OEMs a data-driven way to make vehicles safer, more reliable, and personalized, CEO and co-founder David Hallac told FreightWaves. The team’s machine learning software aggregates data generated by millions of vehicles to help to offer predictive maintenance, personalized in-vehicle experiences, usage-based insurance and more.
“Our focus is around the influx in data that has been generated and the near-term use cases and applicability that large-scale number crunching can enable,” Hallac said.
The company’s machine learning software can be applied to passenger cars, trucks, marine vehicles, and agriculture machinery, and the company is already working with half a dozen passenger car and commercial truck manufacturers globally, deploying its software in over 500,000 commercial trucks in North America and Europe, according to Hallac.
Trucks collect better and richer data than passenger vehicles, he said, yielding more use cases ready to be leveraged, such as solving drowsy driver detection.
Elaborating on the predictive maintenance solution, Hallac said the data can be leveraged to identify which specific components on which specific trucks are likely to fail, aiding fleet owners and helping manufacturers “design the next generation of vehicles.”
Acknowledging the large number of startups playing in the connected vehicle space, he said in a “bake-off” with existing solutions, Viaduct’s software predicting which vehicles are likely to fail was “an order of magnitude better than the state-of the art.”
For that success rate he credited the team’s “rock-star” machine learning team, formed while members were conducting connected vehicle research at Stanford.
The research eventually turned into Viaduct, founded in 2018. Company leaders includes former and current professors from Stanford and Georgia Tech, as well as experts in machine learning who have worked at Tesla, Facebook, Google Brain, Medallia and Boeing.
Hallc said Viaduct will use the new funding to work on integrated solutions to larger scale machine-learning problems. “We need to build them out at scale,” he said, “and aggregate them into a turn-key solution rather than an ad hoc use-case-by-use-case application.”
