Arrakis emerges from stealth with $38M to bring AI to factories and supply chains

Arrakis Secures $38 Million to Target Industrial Operations

Arrakis, a London and Paris-based startup, has emerged from stealth with $38 million in total funding to build what it describes as an AI operating system for industrial sectors. The company raised a $30 million Series A led by Blossom Capital, following a $7.5 million seed round led by Accel that closed in March. The Series A values Arrakis at $140 million post-money, according to Fortune2

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. The startup's central thesis challenges conventional wisdom: the biggest returns from artificial intelligence will come from AI for factories and supply chains, not from office software1

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CEO Rafael Quintanilla, a former vice president at Accel, co-founded Arrakis in January 2026 with Haroun Beltaifa and Romain Fouilland, both formerly of Palantir, and Mikhail Galkov, previously of Delivery Hero. Quintanilla explained his motivation: "Most AI investment to date has targeted the 30% of workers behind a desk. The real ROI lies in the 70% running industrial operations"2

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. The angel investor list includes Datadog CEO Olivier Pomel, OpenAI head of business products Olivier Godement, and Junaid Hussein, founder of Cambridge Aerospace1

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Forward-Deployed AI Engineers Embed at Customer Sites

Arrakis deploys forward-deployed AI engineers who embed directly at customer sites in sectors like aerospace, energy, logistics, and manufacturing. This hands-on approach differentiates the startup from traditional consulting firms that charge for headcount rather than outcomes. The company ties roughly half its fees to performance targets, an unusual structure in enterprise software that Quintanilla frames as proof the system delivers measurable results1

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. Arrakis says it already has five paying customers, including NYSE-listed enterprises, and that one client cut procurement cycle times by 90 percent using its platform1

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For one New York-listed shipping company, the goal was to improve cash-flow visibility from monthly to daily. Arrakis's engineers rebuilt the spreadsheet operators already used, having AI populate the data while the system "learns and starts to codify the knowledge of those operators" as they make corrections2

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. The playbook, Quintanilla said, "always starts with HQ, prove the value, move to field operations as soon as you get the pull to get there"2

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Model-Agnostic Approach Cuts Token Costs by 70 Percent

Rather than locking customers into a single model provider, Arrakis takes a model-agnostic approach that resonates with executives worried about vendor lock-in. The company typically starts building using commercial models from OpenAI and Anthropic before shifting workloads to open-source alternatives from vendors like Mistral, which recently acquired industrial AI firm Emmi to strengthen its own pitch to manufacturers1

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. Quintanilla said one Swiss C-suite executive told him: "When we started this, everyone told us we had to be on Copilot. Then we went to OpenAI. Now it's Anthropic. My head is going like this... I basically want someone who is able to route me to the best provider"2

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The company claims this flexibility delivers a two-to-four-fold improvement in output quality while cutting token costs by roughly 70 percent1

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. This approach positions Arrakis as what Quintanilla describes as an AI layer for key operations of industrial companies, handling everything around core engineering functions2

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Positioning Against Palantir and Consulting Giants

The founding team's Palantir pedigree is deliberate. Quintanilla has said the company sees Palantir as a legacy player ripe for disruption, noting that "half of my team currently comes from Palantir," including a former head of Palantir's procurement and supply-chain team2

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. He argues that Palantir "is a 20-year-old company that has a very hefty price point, that has a technology that is starting to become legacy"2

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Arrakis also positions itself against consulting giants like Accenture and Boston Consulting Group. Quintanilla is skeptical of the sweeping "process transformation" that consultants often sell, noting "there is a lot of fatigue from CEOs on having vendors that do not want to commit to short timeline[s]"2

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. The difference, he argues, is speed: Arrakis can deploy within weeks rather than the months or years that legacy vendors require1

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Expansion Plans Target Family-Controlled Businesses

Arrakis has found its best traction with family-controlled businesses, which tend to make faster purchasing decisions than publicly traded corporations with layered approval processes. Quintanilla called this "an open secret," explaining: "They think long term, they can push for top-down initiatives to be executed, and I can build non-transactional relationship[s] with those people"2

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The company plans to triple its headcount from about 15 employees and open offices in New York and the Middle East, using the fresh capital to expand its presence in markets where industrial transformation is a government priority1

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. Whether Arrakis can scale its forward-deployed model without ballooning costs will test whether its approach works beyond its first handful of clients, particularly as it competes in a crowded but fast-growing market for industrial AI against well-funded competitors like PhysicsX, which raised $300 million at nearly $2.5 billion valuation in June, and Jeff Bezos-backed Prometheus1

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