Supply chain startup Atomic came out of stealth last year with founders who promised to use their experience at Tesla to streamline inventory and boost customers’ bottom lines.
At its core, Atomic decides how much inventory a company should have, and where, by simulating scenarios, then recommending, or even automatically choosing, a response. The approach traces back to a crisis. Atomic’s founders built an early version of this system at Tesla during the 2018 Model 3 production ramp, when the automaker’s own spreadsheets couldn’t keep up with how quickly planning needed to change.
But in the year-plus since Atomic co-founders Michael Rossiter and Neal Suidan started talking publicly about their work, that shift has become real for customers — including big tech companies like DoorDash and HelloFresh. It has paid off financially, too. Atomic’s annual recurring revenue has quintupled since the beginning of this year, according to Jon McNeill, a former Tesla president and the founder of DVx Ventures, where Atomic was incubated.
That growth just helped Boston-based Atomic lock down a $12.5 million Series A funding round, bringing its total funding to just north of $15 million to date. The new round was led by growth equity firm Klass Capital and Seattle VC stalwart Madrona Venture Group. Atomic has also brought on longtime Tesla planning director Jeff Goodrich as its CTO and third co-founder.
“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, who is Atomic’s CEO, said in an exclusive interview with TechCrunch. “AI can play the role of finding all of the best paths through that forest.”
“The company has transitioned from pilot customers into real customers, and by real customers, it’s DoorDash-scale customers,” said McNeill, who’s also on Atomic’s board, in an interview. “The product has evolved from being an optimization platform that gives recommendations to a platform that not only gives recommendations but it makes decisions, so it’s fully autonomous in that sense, and so DoorDash is running, I think, 90% of its purchasing across hundreds of sites.”
For food-focused customers like DoorDash, for instance, Atomic’s software helps cut down on waste and spoilage. And each new industry Atomic works in presents different challenges, Rossiter said.
“The cool thing about Atomic is it’s a general model of how you think about supply chains and operating models, and so no matter what that system looks like, our AI can can adapt to it and tailor fit it,” he said. “We’re working with CPG [consumer packaged goods], we’re going deep with mobility and manufacturing clients right now as well, and working that space, kind of going back to our Tesla roots.”
Making the agentic software useful and adaptable for multiple industries was a big part of what drew investor interest for the Series A, Rossiter said. But it was also Atomic’s ability to deploy quickly with new customers.
“We gave them this challenge from a board level of compressing their onboarding time and really making it a non-event for a customer to turn this on,” McNeill said. Suidan, who is also Atomic’s chief product officer, ran point on that challenge, McNeill said. He was able to push Atomic’s agentic AI to the point it was able to figure out the “decision rules” that a customer’s staff might have, even if they hadn’t been written down anywhere.
“Then customers were saying, ‘Okay, then you might as well make the decision and free my time up,’” McNeill said. “And where executives, I think, kind of got it was — decision speed is an advantage in any business. And this was one of our first principles at Tesla. When I got to know Elon, he said the thing that will separate us from all of our competitors is decision speed, because decision speed compounds. Like, I make a decision today, I build on that decision tomorrow, et cetera, and it takes one of our competitors, like Ford or Toyota, 30 days to make the first decision.”
Rossiter said he’s excited to help pull customers’ supply chain efforts out of spreadsheets and into advanced software that can help make planning decisions. It’s an evolution he’s seen CFOs lead for their own organizations, but he said it’s rarer to find someone doing the same for operations.
“Finance data always gets the priority. Operating data doesn’t always get that,” he said.