Atomic secures $12.5 million for autonomous supply chain planning

Boston-based supply chain software startup Atomic has raised a $12.5 million Series A round, taking its total funding to just over $15 million. The company, founded by former Tesla employees Michael Rossiter and Neal Suidan, uses AI to determine how much inventory an organisation should hold and where it should be positioned.

Klass Capital and Madrona Venture Group led the financing. Atomic has also named longtime Tesla planning director Jeff Goodrich as chief technology officer and third co-founder. The company says its annual recurring revenue has quintupled since the beginning of the year.

From recommendations to automated decisions

Atomic models supply-chain scenarios to identify possible responses. Its software can recommend actions or select them automatically, moving beyond a conventional optimisation system that leaves every operational decision with a planner.

Jon McNeill, founder of Atomic incubator DVx Ventures and a member of the startup's board, said the product has progressed from pilot projects to deployments with large customers. He said DoorDash is using Atomic for roughly 90% of purchasing across hundreds of locations.

For food-oriented businesses, the platform is intended to reduce waste and spoilage by improving purchasing and inventory decisions. Rossiter said Atomic is also working with consumer packaged goods businesses, mobility companies and manufacturing clients, where each operating model brings different planning constraints.

Tesla experience shapes the product

The founders developed an early version of the approach at Tesla during the 2018 Model 3 production ramp. Planning requirements were changing quickly enough that the automaker's spreadsheets could not keep up, creating the need for a system that could evaluate a much wider set of inventory and operational choices.

Rossiter describes supply-chain management as a continuously changing optimisation problem: companies must assess the decisions available at a given moment while conditions evolve. Atomic positions its AI as a way to find viable paths through that changing set of choices.

Faster onboarding is part of the strategy

Investor interest also reflected Atomic's effort to make deployments faster. McNeill said the company was challenged to compress onboarding so that activating the software would become a minor event for customers rather than a lengthy implementation.

Suidan led work to push the agentic system toward identifying a customer's decision rules, including rules that may exist in staff practice but have never been formally documented. McNeill said customers then began asking the platform to make the decisions and release staff time for other work.

Atomic's expansion illustrates a practical shift for operations leaders: moving supply-chain planning out of spreadsheets requires not only better forecasting, but clear confidence in which decisions can be learned, reviewed and safely automated at scale.