A startup using AI to simulate emission levels for fleet vehicle trips has closed a $4.3m (£3.4m) seed round.
Founded in 2021, Clearly has developed a climate intelligence platform that it says can help fleet operators meet net zero targets.
With the transport sector accounting for 25% of global emissions, decarbonising supply chains is a key focus for reducing CO2 in the atmosphere.
However, achieving net-zero goals in road transportation alone requires an annual investment of $1.75tn, according to some research, which is why more than half of CEOs are focused on improving data visibility to better manage and reduce emissions.
Clearly combines vehicle GPS, fuel, energy and operational data, such as package weight, to simulate emissions so that fleet operators can make informed decisions for meeting net-zero goals.
Founder and CEO Danielle Walsh claims that these real-time insights help operators identify and choose the most effective decarbonisation initiatives and facilitate access to financing for these initiatives.
The new investment, led by Pace Ventures and Nine Realms, will go towards growing the company’s existing product offering and adding to its suite of proprietary AI capabilities.
It also saw participation from existing mobility investors Mobilion, Next Gear and M1720 alongside notable angels Lord Nash and Margaux Primat.
Clearly added that it will increase its headcount to meet demand for its product.
Walsh said: “Decarbonising supply chains is not a new challenge, but one of the largest hurdles for businesses has been accessing and analysing comprehensive data, as a direct result of supply chain complexities and the nature in which this data has been collected up until now.
“We saw that by using our unique approach to collect, normalise and blend supply chain data, we could improve its interoperability and use it to provide actionable insights on transportation emissions down to the level of individual trips and packages.”
“We are deliberately hardware-agnostic, which means our platform is compatible with any data source, overcoming the significant initial challenge of data acquisition,” she added.