Nexterity wants to automate the hard, dangerous part of pipefitting; plus, Feather is building the ‘Android of robotics’ for developers

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1:13That's Framer.com slash tcstartups. Rules and restrictions may apply. Lindsay Elliott is big into bolts. At last year's Bolting Symposium, the 13th annual one of those, she said the highlight was playing Bolting Bingo against the many self-proclaimed torque dorks who were in the room. A former engineer and planner at ExxonMobil, Elliot has spent years thinking about how to improve the infrastructure that moves oil, gas, and petrochemicals. Bolts are what she landed on. Specifically, the bolts that connect sections of pipe, technically called bolted flange joints. These bolts require hard physical work to loosen and tighten and are the source of many pipe fitters' injuries.

1:59Like many trade industries, there's also a labor shortage. In an interview with TechCrunch, she said, Those people get really tired when they're asked to work 12 hours a day for three months in a row. I've talked to pipefitters across the U.S., across Canada, and just repeatedly have been told North American pipefitting productivity is notoriously low. The solution Elliot came up with at her startup Nexterity, which is one of the startup Battlefield 200 selected to participate in TechCrunch Disrupt, is a remote-controlled robot that can handle that part of the job. It's the kind of idea that could fundamentally change this particular blue-collar job if widely adopted, making the workers safer and more productive.

2:47Think, more dork, less torque. The robot comes in two main pieces that fit around a pipe. Powered by batteries, the robot can slide across the pipe once it's attached and quickly loosen and tighten four bolts at a time. Elliot said Nexterity has developed a few different configurations of the robot to fit different standard pipe sizes, but they're all small enough to fit in a Pelican case and be carried by a single worker. That makes them easy to deploy to new sites, flexibility that is crucial to Nexterity's business model of treating the robot like rental construction equipment. Elliot said she arrived at this particular design as a result of conversations she's had over the last few years not just at the Bolting Symposium, but also with members of the Pressure Vessels and Piping Division of the American Society of Mechanical Engineers.

3:41She said, What I learned from the people, the torque dorks per se, is that 80 % of our pipes are between 2 to 8 inches in diameter, or what they call NPS2 to NPS8. And so when you have that much repeatability, you have a fantastic candidate for automation. And it's a pretty straightforward idea. but one that Elliott believes has a lot of upside. She said, I think it would shock a lot of people just how big this market is. I mean, day to day, most of us don't think about pipe infrastructure, but even water, wastewater, water treatment, food and beverage, mining, nuclear, any kind of green and sustainable manufacturing facility, they all use the same kind of piping.

4:27If there is one thing robotics founders and investors agree on, it's that the chat GPT moment where a general-purpose robot can seamlessly adapt to any environment has not yet arrived. Opinions vary on whether the breakthrough is just around the corner or a decade away. Feather Robotics, a humanoid startup founded last year, is developing a robot for either timeline. Unlike Tesla or Figure, which are tackling the lofty mission of building both the body and a foundational brain that is not yet widely deployed, Feather provides the hardware and software toolkit for developers to tackle real-world tasks now.

5:09Feather co-founder Hoa Mai told TechCrunch, You can't buy a Tesla robot today and develop on top of it. We realize that this is not how most companies became successful. Hardware players like NVIDIA or Apple started with a product that worked and was deployable, and then they added complexity over time. Last year, after his previous humanoid startup was sold to OneX, Mai teamed up with Parsa Bakhtiari, a former Tesla Model 3 engineer, who at one point reported directly to Elon Musk to build what the duo hopes will become the Android of robotics. That vision was attractive to Gradient Ventures, which backed Feather at its inception, leading the startup's previously announced$7.6 million pre-seed round.

5:58Since then, Feather has rolled out a modular robotic system that allows developers to customize the hardware for different use cases, such as adjusting arm lengths. The startup has already begun selling to customers, surpassing$1 million in revenue. Although Feather is not disclosing its customers, it's said that its robots are working as cooks in restaurants and cleaning up science labs. On the software side, the hardware can run models from any leading robotics AI provider, including NVIDIA, skilled, or physical intelligence. We've been selling small quantities of these robots, Mai said, and now that we've resolved almost all the issues over the last year of field testing, we are getting ready for a big product launch.

6:42According to Darian Shirazi, general partner at Gradient, Feather does not have direct competitors in the U.S. He broke down the current hardware robotics landscape into three categories. Startups like Sunday, building domestic household robots, heavyweights like Figure and Tesla, aiming for general-purpose machines, and Feather, which he believes is the only U.S. startup developing a modular humanoid platform. Mai admits that Feather took a page from Chinese robotics companies like Unitree, but with new foreign-made models restricted from entering the U.S., Feather is now uniquely positioned as a homegrown option of its kind.

7:24Feather's other advantage is its price. The robot costs$30 ,000, which is about half the price of Unitree's H2-EDU. Shirazi believes the market size at that price could be very large, saying, you would hire a laborer for$50 ,000 to$60 ,000 a year. You have to train them. They'd have to have HR. They'd have to have all these different support mechanisms. You can now buy a Feather robot to do that. Feather is also operating extremely efficiently, having spent only a fraction of its pre-seed funding. The startup's big bet, of course, is that the value in robotics will come from an ecosystem developed around the hardware.

8:06Mai said, if we think about the market size today for physical AI companies, it's very small. But if you think about how many physical AI application companies will probably exist in five years, we expect it to be in the thousands. Feather hopes to be the platform that powers all of them. That's all for now. For the latest in startup tech news, go to TechCrunch.com.

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