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Atomic Secures $12.5M Series A Funding for AI Supply Chain Software

Supply chain startup Atomic, founded by former Tesla team members, has raised $12.5 million in Series A funding, bringing its total funding to over $15 million.

  • Atomic's agentic AI software helps companies manage inventory by simulating scenarios and making decisions.
  • The company's annual recurring revenue has quintupled since the beginning of this year.
  • Customers like DoorDash and HelloFresh are using Atomic's software, with DoorDash reportedly running 90% of its purchasing across hundreds of sites through the platform.

Boston-based supply chain startup Atomic has successfully closed a $12.5 million Series A funding round. This new investment, led by Klass Capital and Madrona Venture Group, increases Atomic's total funding to just over $15 million.

Atomic's software, developed by co-founders Michael Rossiter and Neal Suidan, who previously worked at Tesla, uses agentic artificial intelligence to determine optimal inventory levels and locations. The system simulates various scenarios and then recommends or automatically implements responses. This approach was initially developed at Tesla during the 2018 Model 3 production ramp to manage rapidly changing planning needs.

The company's annual recurring revenue has quintupled since the start of this year, according to Jon McNeill, a former Tesla president and founder of DVx Ventures, where Atomic was incubated. Major companies such as DoorDash and HelloFresh are now utilising Atomic's platform. DoorDash is reportedly using the software for 90% of its purchasing across hundreds of sites.

Jeff Goodrich, a long-time Tesla planning director, has also joined Atomic as its CTO and third co-founder. Atomic's CEO, Michael Rossiter, stated that AI can find the best paths through the complex optimization challenges of running a supply chain.

Why this matters: The funding and adoption by large companies indicate a growing interest in AI-driven solutions for complex supply chain management, potentially leading to increased efficiency and reduced waste.

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