The best path to successfully deploying a robot is not building one at all, according to Destro, a startup that came out of stealth Tuesday with an $8 million seed round.

Most new robotics companies are focused on finding the right form factor or developing an AI model that can put metal hands to work. Destro has instead built an AI intelligence layer that lets robots work effectively in logistics settings, in part by also telling the human workers what to do.

“A lot of robotics companies started from robotics engineers [asking] ‘What cool things I can do?’” Destro founder Manthan Pawar, a veteran of the industry, told TechCrunch. “One of the biggest reasons we are winning against robotics companies is because we are not a robotics company.”

Pawar, who earned a master’s degree in robotics at NYU Tandon and has spent roughly eight years in the U.S. supply chain and robotics industry, explains that “our mindset is, we know our customers’ problems so damn well, and we are actually on path to be cash flow positive at the end of this year.”

Richard Brunelle, the director of automation for the American logistics group at Yusen Logistics, a South Korean shipping giant, helped get the startup pointed in the right direction. Brunelle is responsible for automation across about 30 facilities in the U.S. There, Yusen uses fixed automation, like conveyors and sorters, but it is still piloting new technology like trailer-unloading robots and autonomous floor scrubbers.

Finding more ways to put technology like that to work is Brunelle’s priority: Yusen’s UK subsidiary has built out a fully autonomous facility and now a similar plan is in the works in the U.S. When Brunelle met Pawar, Destro was focused on a different challenge in the space—picking and pack, the process by which various goods are sorted into single packages.

Brunelle realized his primary challenge was “fundamentally the same problem.” His job involved cross-docking: unloading goods from one truck and sorting them into mixed loads for other trucks that make the final delivery to customers.

“I asked whether Destro would be willing to adapt their solution to fit that cross-dock environment, because I don’t think anyone was doing that,” he told TechCrunch. “They went away, thought it through, and came back excited. They agreed nobody was addressing that space and that they could modify their tool to support it. Since then, they’ve gone all in.”

Destro started with a pilot program at one Yusen facility in the Pacific northwest, using three cart-moving robots built by Miva Robotics and operated by Destro’s Vision operating system based on open-weight vision-language-action models (AI systems that interpret camera images and instructions to control a robot’s movements).

As human workers unload goods from one truck into different carts, the robots find the full loads and bring them to their destinations. What makes this efficient, in the estimation of Brunelle and Pawar, is that the human, the cart, and the trucks are all directed by Destro’s Mothership operating system.

“We make that operation less labor intensive, and we get away from the paper,” Brunelle said. “Everything is now systematic.”

That matters because Yusen also talked to two other big-name robot startups in this space, and neither could fit into their workflow. One offered a robot that could move the carts point-to-point but could not manage loading or unloading. The other came with fleet management tools, but required a person to handle all the orchestration. Destro won because of its ability to apply autonomous direction to the whole process.

Now, Destro is expanding its initial pilot to a full deployment of 26 robots and launching another pilot with 17 robots at Yusen’s facility in Southern California. Pawar plans to take this cross-dock loading workflow and “copy-paste” across thousands of other warehouses that handle this kind of labor. It’s that plan that convinced Base10 Partners and Bonfire Ventures to lead Destro’s seed round, with additional investment from CoFound Partners.

Destro may face a challenge with workflows that require more dexterity and manipulation. Generic robot bodies and open-source models haven’t proven capable at these tasks yet, and it’s not clear if companies building foundation models, ultra-dexterous hands, or general-purpose humanoids will make those tools available to a company like Destro rather than trying to capture that business themselves.

Pawar remains confident that he’s found the part of the stack where value will accrue, and that his company will be able to take advantage of the research dollars pouring into new AI models and robot components.

“Robots are a platform. Every layer model is a platform. But we build a harness around it,” Pawar told TechCrunch. “That harness is just so complex and value-added that without that harness, these workflows are completely impossible, right?”

For now, competing with futuristic robot-builders is probably not an issue. Brunelle says he has yet to find a good use case for a bipedal humanoid robot, though he is evaluating a potential pilot with a wheeled humanoid.

“At the end of the day, we’re not putting automation into a building just because the technology is interesting,” Brunelle said. “It must solve a real operational problem. If it can make the operation more efficient, consistent, and flexible, that’s ultimately going to benefit our customers.”

Destro will be making its case for the non-robot robot company at TechCrunch Disrupt in just a few weeks. Join us in October to see Destro in person, along with the rest of our Battlefield competitors.

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Tim Fernholz
Tim Fernholz is a journalist who writes about technology, finance and public policy. He has closely covered the rise of the private space industry and is the author of Rocket Billionaires: Elon Musk, Jeff Bezos and the New Space Race. Formerly, he was a senior reporter at Quartz, the global business news site, for more than a decade, and began his career as a political reporter in Washington, D.C. You can contact or verify outreach from Tim by emailing [email protected] or via an encrypted message to tim_fernholz.21 on Signal.
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