Camion raises €2.7M to scale the deployment of EV charging

Camion, a power and electric vehicle charging intelligence and analytics platform based in London, arms stakeholders in the real estate and EV charging infrastructure sectors with crucial insights to capitalise on the increasing demand for EV charging and future-proof their portfolios.

The company has successfully raised 2.7 million in a pre-seed funding round, spearheaded by EQT Ventures. First Look Capital and RitMir Ventures also participated, along with distinguished angel investor Chris Adelsbach. Comprising energy and real estate experts, the Camion team will utilise this investment to enhance its engineering, machine learning, and data science capabilities to expand its platform.

Experts estimate that a $1.9 trillion investment in charging infrastructure is necessary to meet net-zero commitments by 2050. For effective deployment, developers must quickly identify and develop land at the nexus of charging demand and high-power availability from local grid operators. Properties at these strategic locations will become increasingly sought after as the need for widespread electrification escalates.

Camion merges property and location data with insights on power supply, traffic patterns, and future local energy demands, enabling various market players to pinpoint the best sites based on their power requirements.

The real estate sector faces escalating power demands, partly due to net-zero commitments and the increasing daily power needs for vehicle charging and building operations. Many investors in infrastructure and real estate are unaware of the potential future risks and opportunities. Camion fills a critical niche by integrating a wealth of essential data with proprietary analytics.

Real estate owners and investors equipped with the technology to understand the value of this infrastructure could potentially earn billions in annual rental income and property appreciation. Conversely, properties unprepared for this shift risk becoming stranded assets, as commercial occupiers and drivers increasingly demand EV charging and broader electrification. Prior to Camion, no unified platform existed to help landowners and infrastructure providers identify these key properties.

Camion’s platform assesses properties based on their electrification readiness and potential, offering powerful insights that enable users to swiftly capitalise on the burgeoning demand for EV charging infrastructure. It enables real estate owners, investors, lenders, and infrastructure developers to identify and rapidly evaluate properties primed for the energy transition before committing capital.

The platform also tracks the escalating electricity needs of communities as the energy transition progresses, safeguarding and augmenting property values as access to this infrastructure becomes essential. On a broader scale, Camion’s platform aligns incentives, unlocking and protecting trillions in potential value, mitigating risks to property value, and aiding real estate owners and infrastructure developers in deploying infrastructure comprehensively.

Jacob Monroe, Founder and CEO at Camion, commented: “The structural shift toward electrification is a huge opportunity for those who act swiftly to understand and deploy electric vehicle charging infrastructure where it is needed. As energy demand and generation become more distributed, electrified real estate will become the next great asset class in the $50 trillion global commercial real estate market. Camion exists to supercharge this once-in-a-century transition through a blend of machine learning, big data, and extensive industry insights.”

Sandra Malmberg, Partner at EQT Ventures, added: “With increasing EV adoption, the real estate sector has the opportunity to become the new “gas station” for EVs while increasing the value of properties for asset owners and developers.

“There is no question that the real estate industry is rapidly moving towards widespread electrification, and Camion’s platform is removing bottlenecks along the way to scale."