Insider Brief
- Slamcore has raised $14 million in funding led by ROKStar Ventures, bringing its total funding to $40 million, with participation from Toyota Ventures, Interwoven Ventures, MMC Ventures, Amadeus Capital Partners and IP Group.
- The London-based company develops visual AI software that enables industrial vehicles to track their position and movement inside facilities without GPS or other infrastructure, providing real-time visibility into vehicle activity, fleet utilization and safety risks.
- Slamcore said data generated from its deployments could help train future physical AI and robotics systems, while the new funding will support expansion across manufacturing, warehousing and logistics operations.
Spatial intelligence software company Slamcore has raised $14 million in new funding led by ROKStar Ventures, a subsidiary of industrial automation giant Rockwell Automation, bringing the company’s total funding to $40 million.
According to the company, the round also included existing backers Toyota Ventures, Interwoven Ventures, MMC Ventures, Amadeus Capital Partners and IP Group. The new capital will support continued deployment of Slamcore’s software platform as the company expands in the manufacturing, warehousing and logistics space.
Rockwell’s VP of robotics Ryan Gariepy said deploying computer vision systems that work reliably in large, busy industrial environments remains a difficult challenge, noting that many existing solutions either require costly infrastructure upgrades or struggle to perform consistently amid the constantly changing conditions of active factories and distribution centers.
“The potential for the same technology platform to work on every class of autonomous and human-operated industrial vehicle is key,” Gariepy said. “We’re also incredibly excited about their ability to scale without requiring complex and time-consuming vehicle or facility redesigns.”
What Does Slamcore Do?
The London-based Slamcore develops visual AI software that enables industrial vehicles, such as forklifts, to determine their position and movement inside facilities without relying on GPS, beacons, floor markers or other infrastructure. Its technology uses stereo cameras and computer vision to track vehicle location and activity in real time.
Slamcore said the technology can be deployed across both manually operated and autonomous industrial vehicles without requiring significant facility modifications, allowing operators to improve use of their fleets, investigate incidents more quickly and identify operational issues.
Slamcore CEO Owen Nicholson noted many manually operated vehicle fleets in factories and warehouses remain largely untracked in real time, creating a persistent blind spot the technology is built to address. The company cited industry estimates showing tens of thousands of forklift-related injuries annually in the U.S. and said many facilities still lack visibility into vehicle location, performance and utilization.
“Slamcore Aware and Slamcore Alert change that from day one, without disruption to existing operations,” Nicholson said. “ROKStar Ventures’ investment tells us that the industry’s most sophisticated players see this as a foundational infrastructure, not just another point solution. As our footprint grows, so does a body of real-world operational data that does not exist anywhere else and that will become the backbone for the next generation of physical AI.”
Creating Data for Physical AI and Robotics
The company indicated it sees long-term value in the operational data generated by its deployments. As more vehicles are connected to the platform, Slamcore is building what it describes as a growing dataset of real-world industrial operations that could support future physical AI and robotics applications.
“At Toyota Ventures, we believe safety and efficiency go hand-in-hand,” added Jim Adler, founder and general partner at Toyota Ventures and a Slamcore board member. “Slamcore Aware and Alert have proven this today, but their long-term potential is even more compelling. Each Slamcore deployment generates real-world operational data, which will train the next generation of physical AI models.”
