Archetype AI has successfully raised $35 million in Series A funding to advance the deployment of its innovative “Physical Agents,” which aim to tackle real-world challenges. The funding round was led by IAG Capital Partners and Hitachi Ventures, with participation from prominent investors such as Bezos Expeditions, Venrock, and the Amazon Industrial Innovation Fund.
The company is at the forefront of developing physical AI technologies designed to sense, understand, and act in various environments. According to Dennis Sacha, founding partner at IAG Capital Partners, “Archetype AI is refining and defining the full stack of Physical AI, creating scalable solutions that operate in the real world, not just on screens or in simulations.” He emphasized the potential for these technologies to redefine interactions between humans and agents across diverse applications, from edge devices to critical infrastructure.
While AI agents have increasingly automated digital workflows, extending their capabilities to the physical realm has posed significant challenges. Traditional solutions often rely on specific industry applications or custom machine learning tools, which require extensive engineering expertise and substantial capital. These methods typically address narrow problems, such as safety, without the flexibility to adapt across various real-world scenarios.
Archetype’s Physical Agents are designed to bridge this gap, allowing businesses to convert raw sensor data into actionable intelligence quickly. Users can employ natural language prompts and APIs that integrate seamlessly with existing systems, enhancing efficiency and effectiveness. The agents leverage Newton, a groundbreaking physical AI foundation model, to combine multimodal sensor data, video feeds, and contextual information, yielding valuable insights and recommendations.
The Archetype platform includes pre-built services such as the Agent Toolkit, which facilitates the rapid assembly, testing, and deployment of Physical Agents. These agents can function in various environments, including private clouds, on-premises, or on the edge, ensuring data sovereignty and enterprise-grade security—essential factors for industries operating in the physical space.
“Physical Agents allow businesses to move from intent to action with speed and efficiency that were not previously possible,” said Ivan Poupyrev, co-founder and CEO of Archetype AI. He explained that Newton provides a generalized physical intelligence, while the Archetype platform simplifies the creation of custom solutions tailored to specific operational needs.
To further accelerate development, Archetype offers ready-to-use agents that cater to a range of applications. This flexibility enables customers to deploy solutions that are specifically designed for their operations, ultimately enhancing productivity and safety.
Early adopters of Archetype’s technology, including NTT DATA, Kajima, and the City of Bellevue, have successfully implemented Physical Agents to streamline operations and improve safety across various settings, from warehouses to construction sites. A representative from Samsung Ventures remarked, “Archetype AI’s Physical Agents improve operations and safety across real-world assets. Their platform delivers tangible results enterprises can put into action immediately.”
The recent funding will enable Archetype to further scale its platform, enhance the capabilities of its Physical Agents, and invest in ongoing research and development. The company is also set to release new research demonstrating the advanced capabilities of Newton in interpreting and acting upon physical signals. This research represents a significant step in moving beyond mere understanding to effectively manipulating the physical environment.
Currently, the Archetype AI Platform and Physical Agent Toolkit are available in beta for select customers, with expanded features expected to roll out in the coming months. As the demand for effective solutions in real-world applications continues to grow, Archetype AI is poised to lead the charge in this transformative field.
