供应链管理初创公司 Atomic 去年正式公开亮相，其创始人表示将利用他们在特斯拉的工作经验来优化库存管理，从而提升客户的盈利能力。
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.
Atomic 的核心功能是：通过模拟各种情景，为公司确定应持有的库存数量及库存存放地点，并据此提出相应的管理建议（甚至可以自动做出决策）。这一技术的起源可以追溯到 2018 年特斯拉 Model 3 生产高峰期——当时特斯拉自家的电子表格系统无法满足快速变化的计划需求，Atomic 的创始人便开发出了该系统的早期版本。
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.
自 Atomic 的联合创始人 Michael Rossiter 和 Neal Suidan 开始公开介绍他们的这项技术以来，许多企业（包括 DoorDash 和 HelloFresh 等大型科技公司）已经开始实际应用该系统。从财务角度来看，这一投资也取得了显著回报：根据前特斯拉总裁、DVx Ventures 创始人 Jon McNeill 的介绍，Atomic 今年的年度经常性收入已经增长了五倍。
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.
凭借这一强劲的增长势头，总部位于波士顿的 Atomic 成功筹集了 1250 万美元的 A 轮融资，使其累计融资总额达到了近 1500 万美元。此次融资由成长型股权投资公司 Klass Capital 和西雅图的知名风险投资机构 Madrona Venture Group 领投。此外，Atomic 还聘请了特斯拉前规划总监 Jeff Goodrich 担任公司的首席技术官（CTO）及第三位联合创始人。
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.
“如果你考虑管理供应链或运营模式的话，其实就相当于在一片‘无限大的搜索空间’中寻找最优解——你需要不断思考在任何时刻可以做出的所有决策，而这些决策本身也在不断变化，”Atomic公司的首席执行官Rossiter在接受TechCrunch独家采访时说道。“人工智能可以在这个过程中帮助你找到所有可能的最佳路径。”
“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.”
“该公司已经从最初的试点客户发展到了真正的商业客户，而这些‘真正的客户’其实都是像DoorDash这样的大型企业，”同样担任Atomic董事会成员的McNeill在采访中表示。“我们的产品已经从一个仅仅提供优化建议的平台，进化为一个不仅能提供建议、还能自主做出决策的平台；因此，我认为DoorDash现在在数百个采购渠道中90%的采购工作都是通过我们的系统来完成的。”
“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.”
对于像DoorDash这样以食品配送为核心业务的客户来说，Atomic的软件有助于减少浪费和食品变质的情况。Rossiter指出，Atomic进入的每一个新行业都会面临不同的挑战。
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.
“Atomic的独特之处在于它提供了一种通用的方法来管理供应链和运营模式；无论系统的具体结构如何，我们的AI技术都能适应并对其进行优化，”Rossiter继续说道。“我们目前正在与消费品制造企业（CPG）合作，同时也在深入拓展移动服务和制造业领域的应用，这某种程度上让我们回到了公司的‘特斯拉式’创新根基上。”
“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.”
Rossiter认为，正是这种让软件具备跨行业适用性和灵活性的特点，吸引了投资者对Atomic A轮融资的兴趣；此外，Atomic能够迅速与新客户建立合作关系，也是其吸引投资的重要因素之一。
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.
麦克尼尔表示：“我们从董事会层面提出了这一挑战，要求压缩客户的上手时间，让客户开启这项功能真正成为一件无感之事。”麦克尼尔说，兼任Atomic首席产品官的苏伊丹负责牵头应对这一挑战。他成功将Atomic的代理式AI推进到能够推断出客户员工可能拥有的“决策规则”的程度，即便这些规则从未被记录下来。
“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.
麦克尼尔说：“后来客户说，‘好吧，那你干脆帮我把决策也做了，解放我的时间。’而高管们真正领悟到的是——决策速度在任何业务中都是一种优势。这也是我们在特斯拉的核心理念之一。当我认识埃隆时，他说，让我们与所有竞争对手拉开差距的，就是决策速度，因为决策速度会产生复利效应。比如，我今天做一个决策，明天在这个决策基础上再做下一个，以此类推。而我们的竞争对手，比如福特或丰田，做第一个决策就要花30天。”
“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.”
罗西特表示，他很兴奋能帮助客户将供应链工作从电子表格中解放出来，转入能够辅助制定规划决策的先进软件。他说，这是他已经看到CFO们在自己组织中引领的变革，但他表示，很少有人对运营做同样的事情。“财务数据总是优先获得关注。运营数据却未必如此，”他说。
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.