Ivan Poupyrev
Since founding Archetype AI, we've been driven by a simple mission: to build general physical intelligence that helps humanity make sense of the world and solve real-world problems. Today, I'm excited to announce two major milestones on that journey.
First, we've raised $35M in Series A funding, led by IAG Capital Partners and Hitachi Ventures, with participation from new and existing investors including Bezos Expeditions, Venrock, Amazon Industrial Innovation Fund, Samsung, E12, Systemiq Capital, HLV, Gaingels, Plug and Play Ventures, and others. This investment enables us to scale and accelerate the deployment of physical intelligence for our customers — and, most importantly, to continue advancing Newton, our Physical AI foundation model that understands the physical world.
Second, we are launching — and making available to select customers — the Archetype platform and Agent Toolkit, a new suite of tools that empowers organizations to build and deploy Physical Agents on their physical assets, whether it's a factory, a piece of manufacturing equipment, a street intersection, or a fleet of vehicles.
Powered by Newton, Physical Agents fuse multiple streams of real-world sensor data to perceive, understand, and act within real environments. They can be deployed out of the box with little or no additional training and provide localized, context-aware intelligence that helps customers solve tough operational challenges — enabling safer, more efficient operations across manufacturing, smart home devices, telecommunications, energy, construction, logistics, and city infrastructure.
To accelerate adoption, we're launching the Archetype platform with several prebuilt Agents that address common operational needs such as industrial process monitoring, operator task verification, and safety monitoring. All of these can be customized or extended by customers without deep AI expertise and deployed in the cloud, on-premises, or at the edge.
Early customers including NTT DATA, Kajima, the City of Bellevue, and others have already deployed Physical Agents to reduce downtime, improve safety, and increase operational efficiency across warehouses, construction sites, and city infrastructure. Their results validate what we believed from the start: organizations don't need more data — they need intelligence where it matters most: inside their operational environments.
This funding also accelerates our research into advancing Newton as a frontier Physical AI foundation model — massively multimodal, capable of fusing sensor data with natural language, and scaling cross-modal reasoning across increasingly complex environments, tasks, and problems. We're continuing to grow the team and expand partnerships to make Physical AI accessible to every organization that manages physical assets — and ultimately, to bring intelligence to every asset in the physical world.
