{"id":3492039,"date":"2026-09-29T09:00:00","date_gmt":"2026-09-29T09:00:00","guid":{"rendered":"https:\/\/techingeek.com\/index.php\/2026\/09\/29\/former-tesla-group-secures-12-5m-to-automate-supply-chains\/"},"modified":"2026-09-29T09:00:00","modified_gmt":"2026-09-29T09:00:00","slug":"former-tesla-group-secures-12-5m-to-automate-supply-chains","status":"publish","type":"post","link":"https:\/\/techingeek.com\/index.php\/2026\/09\/29\/former-tesla-group-secures-12-5m-to-automate-supply-chains\/","title":{"rendered":"Former Tesla group secures $12.5M to automate supply chains"},"content":{"rendered":"
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Last year, supply chain startup Atomic emerged from stealth mode with founders committed to leveraging their Tesla experience to optimize inventory management and enhance customers\u2019 profitability.<\/p>\n

Atomic fundamentally determines the optimal inventory levels and locations for companies by simulating different scenarios, subsequently recommending or even automatically selecting a course of action. This methodology originated from a crisis, as Atomic\u2019s founders developed an initial version of this system during the 2018 Model 3 production increase at Tesla, when the automaker’s spreadsheets failed to keep pace with the required planning adjustments.<\/p>\n

Over the past year, as Atomic co-founders Michael Rossiter and Neal Suidan began publicly discussing their initiatives, this transformation has materialized for clients \u2014 including major tech players like DoorDash and HelloFresh. Financially, it has yielded substantial returns as well. According to Jon McNeill, a former Tesla president and founder of DVx Ventures, where Atomic was nurtured, the company’s annual recurring revenue has grown fivefold since the start of this year.<\/p>\n

This growth has enabled Boston-based Atomic to secure a $12.5 million Series A funding round, raising its total funding to over $15 million to date. The funding round was spearheaded by growth equity firm Klass Capital and renowned Seattle VC firm Madrona Venture Group. Additionally, Atomic has appointed former Tesla planning director Jeff Goodrich as its CTO and third co-founder.<\/p>\n

\u201cManaging a supply chain and operational model resembles an endless optimization search where you must consider every possible decision at any moment, all while the parameters continuously change,\u201d stated Rossiter, Atomic\u2019s CEO, in an exclusive interview with TechCrunch. \u201cAI can play a vital role in identifying the optimal paths through that complex landscape.\u201d<\/p>\n

\u201cThe company has evolved from pilot customers to authentic customers, with DoorDash-size clients now,\u201d remarked McNeill, who also sits on Atomic\u2019s board, during an interview. \u201cThe product has shifted from a platform that merely provides optimization recommendations to one that autonomously makes decisions, so DoorDash is currently managing around 90% of its purchasing across numerous locations.\u201d<\/p>\n

For food-centric clients like DoorDash, Atomic\u2019s software aids in minimizing waste and spoilage. Rossiter noted that each new sector Atomic engages with brings unique challenges.<\/p>\n

\u201cThe exciting aspect of Atomic is its generalized framework for understanding supply chains and operational models, allowing our AI to adapt and customize accordingly, regardless of the system’s design,\u201d he elaborated. \u201cWe are delving deep into consumer packaged goods, mobility, and manufacturing clients, revisiting our Tesla origins.\u201d<\/p>\n

Creating adaptable software for various industries played a significant role in attracting investor interest for the Series A, Rossiter noted. But it was also Atomic’s swift deployment capabilities with new customers that garnered attention.<\/p>\n

\u201cWe challenged them from the board level to reduce their onboarding duration, ensuring that customers could activate this with minimal disruption,\u201d McNeill commented. Suidan, Atomic\u2019s chief product officer, spearheaded that effort, pushing the boundaries of Atomic\u2019s AI to deduce the \u201cdecision rules\u201d that client personnel might have, even if they weren\u2019t formally documented.<\/p>\n

\u201cThen clients started suggesting, \u2018Well, you might as well make the decision and save me the time,\u2019\u201d McNeill recounted. \u201cExecutives grasped that decision speed is a competitive advantage. It was one of our foundational principles at Tesla. When I connected with Elon, he pointed out that our ability to make quicker decisions would distinguish us from competitors, as decision-making speed accumulates. If I decide today, I build on that decision tomorrow, while it takes competitors like Ford or Toyota thirty days to make their initial choice.\u201d<\/p>\n

Rossiter expressed enthusiasm for transitioning clients\u2019 supply chain initiatives from spreadsheets to sophisticated software that aids in making planning choices. He observed that CFOs have often led this change for their organizations, although it’s less common to see similar advancements in operations.<\/p>\n

\u201cFinancial data always gets prioritized. Operational data doesn\u2019t always receive that same attention,\u201d he remarked.<\/p>\n<\/div>\n

Purchases made through links in our articles may earn us a small commission. This does not impact our editorial independence.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

<\/div>\n
\n

Last year, supply chain startup Atomic emerged from stealth mode with founders committed to leveraging their Tesla experience to optimize inventory management and enhance customers\u2019 profitability.<\/p>\n

Atomic fundamentally determines the optimal inventory levels and locations for companies by simulating different scenarios, subsequently recommending or even automatically selecting a course of action. This methodology originated from a crisis, as Atomic\u2019s founders developed an initial version of this system during the 2018 Model 3 production increase at Tesla, when the automaker’s spreadsheets failed to keep pace with the required planning adjustments.<\/p>\n

Over the past year, as Atomic co-founders Michael Rossiter and Neal Suidan began publicly discussing their initiatives, this transformation has materialized for clients \u2014 including major tech players like DoorDash and HelloFresh. Financially, it has yielded substantial returns as well. According to Jon McNeill, a former Tesla president and founder of DVx Ventures, where Atomic was nurtured, the company’s annual recurring revenue has grown fivefold since the start of this year.<\/p>\n

This growth has enabled Boston-based Atomic to secure a $12.5 million Series A funding round, raising its total funding to over $15 million to date. The funding round was spearheaded by growth equity firm Klass Capital and renowned Seattle VC firm Madrona Venture Group. Additionally, Atomic has appointed former Tesla planning director Jeff Goodrich as its CTO and third co-founder.<\/p>\n

\u201cManaging a supply chain and operational model resembles an endless optimization search where you must consider every possible decision at any moment, all while the parameters continuously change,\u201d stated Rossiter, Atomic\u2019s CEO, in an exclusive interview with TechCrunch. \u201cAI can play a vital role in identifying the optimal paths through that complex landscape.\u201d<\/p>\n

\u201cThe company has evolved from pilot customers to authentic customers, with DoorDash-size clients now,\u201d remarked McNeill, who also sits on Atomic\u2019s board, during an interview. \u201cThe product has shifted from a platform that merely provides optimization recommendations to one that autonomously makes decisions, so DoorDash is currently managing around 90% of its purchasing across numerous locations.\u201d<\/p>\n

For food-centric clients like DoorDash, Atomic\u2019s software aids in minimizing waste and spoilage. Rossiter noted that each new sector Atomic engages with brings unique challenges.<\/p>\n

\u201cThe exciting aspect of Atomic is its generalized framework for understanding supply chains and operational models, allowing our AI to adapt and customize accordingly, regardless of the system’s design,\u201d he elaborated. \u201cWe are delving deep into consumer packaged goods, mobility, and manufacturing clients, revisiting our Tesla origins.\u201d<\/p>\n

Creating adaptable software for various industries played a significant role in attracting investor interest for the Series A, Rossiter noted. But it was also Atomic’s swift deployment capabilities with new customers that garnered attention.<\/p>\n

\u201cWe challenged them from the board level to reduce their onboarding duration, ensuring that customers could activate this with minimal disruption,\u201d McNeill commented. Suidan, Atomic\u2019s chief product officer, spearheaded that effort, pushing the boundaries of Atomic\u2019s AI to deduce the \u201cdecision rules\u201d that client personnel might have, even if they weren\u2019t formally documented.<\/p>\n

\u201cThen clients started suggesting, \u2018Well, you might as well make the decision and save me the time,\u2019\u201d McNeill recounted. \u201cExecutives grasped that decision speed is a competitive advantage. It was one of our foundational principles at Tesla. When I connected with Elon, he pointed out that our ability to make quicker decisions would distinguish us from competitors, as decision-making speed accumulates. If I decide today, I build on that decision tomorrow, while it takes competitors like Ford or Toyota thirty days to make their initial choice.\u201d<\/p>\n

Rossiter expressed enthusiasm for transitioning clients\u2019 supply chain initiatives from spreadsheets to sophisticated software that aids in making planning choices. He observed that CFOs have often led this change for their organizations, although it’s less common to see similar advancements in operations.<\/p>\n

\u201cFinancial data always gets prioritized. Operational data doesn\u2019t always receive that same attention,\u201d he remarked.<\/p>\n<\/div>\n

Purchases made through links in our articles may earn us a small commission. This does not impact our editorial independence.<\/em><\/p>\n","protected":false},"author":2,"featured_media":3492040,"comment_status":"open","ping_status":"closed","sticky":false,"template":"Default","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3492039","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/posts\/3492039"}],"collection":[{"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/comments?post=3492039"}],"version-history":[{"count":0,"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/posts\/3492039\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/media\/3492040"}],"wp:attachment":[{"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/media?parent=3492039"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/categories?post=3492039"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techingeek.com\/index.php\/wp-json\/wp\/v2\/tags?post=3492039"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}