Ex-Tesla team's Atomic raises $12.5M to automate supply chain decisions

The startup says its software determines how much inventory a company should have and where by simulating scenarios, then recommending or automatically choosing a response. The approach traces to a crisis: Atomic's founders built an early version of the system at Tesla during the 2018 Model 3 production ramp, when the automaker's spreadsheets could not keep up with how quickly planning needed to change.

Atomic's growth has accelerated since co-founders Michael Rossiter and Neal Suidan began talking publicly about their work more than a year ago. Annual recurring revenue has quintupled since the beginning of this year, according to Jon McNeill, a former Tesla president and founder of DVx Ventures, where Atomic was incubated. Customers include DoorDash and HelloFresh.

McNeill, who is also on Atomic's board, said in an interview that the company has moved from pilot customers to real customers, describing DoorDash as a DoorDash-scale customer. He said DoorDash is running about 90% of its purchasing across hundreds of sites on Atomic. For food-focused customers such as DoorDash, Rossiter said, the software helps reduce waste and spoilage.

Rossiter, Atomic's CEO, said the company's model is general enough to adapt to different supply chains and operating models. He said Atomic is working with consumer packaged goods companies and going deep with mobility and manufacturing clients, returning to its Tesla roots. Making the agentic software useful and adaptable across industries helped attract investor interest for the Series A, he said, as did Atomic's ability to deploy quickly with new customers.

McNeill said the board challenged Atomic to compress onboarding time and make turning the product on a non-event for customers. Suidan, Atomic's chief product officer, led that effort, McNeill said, pushing the company's agentic AI to figure out customers' decision rules even when those rules had not been written down. Customers then said Atomic might as well make the decision and free up their time, he said.

“If you think about running a supply chain, running an operating model, it's like an infinite search space for optimization that you're trying to figure out all the decisions you could make at any given time — and then it changes all the time too,” Rossiter said in an exclusive interview with TechCrunch. “AI can play the role of finding all of the best paths through that forest.”

McNeill tied the product's value to decision speed. He recalled a lesson from Tesla: “The thing that will separate us from all of our competitors is decision speed, because decision speed compounds,” he said, describing how a decision made today can be built on tomorrow, while competitors may take 30 days to make the first decision. Rossiter said he wants to help pull customers' supply chain efforts out of spreadsheets and into advanced software that can help make planning decisions. He said finance data always gets priority, while operating data does not always get that treatment.