Agility Robotics’ path to Wall Street began long before the current humanoid frenzy. Spun out of Oregon State University in 2015, the company focused on a less glamorous pitch than dancing or acrobatic robots: moving heavy totes through factories and warehouses. Its Digit machines have since been deployed at nine customer facilities, including Amazon, Toyota and GXO.¹

That groundwork culminated this week in a merger with Michael Klein’s Churchill Capital Corp XI, giving Agility the distinction of becoming the first U.S. pure-play humanoid robotics company to trade publicly, under the ticker AGLT. The deal values its existing equity at roughly $2.5 billion and is expected to bring in about $465 million in gross capital before expenses.¹

Chief executive Peggy Johnson casts the listing as a chance to define the commercial category. “There’s something to be said for being first,” she said, arguing Agility can help set the measures customers will demand from humanoids.¹ Her case rests on repetition: Digit can repeatedly lift 50-pound loads that employers may not want workers handling, she told TechCrunch.²

But the public filing turns that confidence into a demanding timetable. Agility reported $1.8 million in revenue last year and a $138.1 million net loss; it used $99.8 million in cash to run the business in 2025. Analyst Michelle Sun warned that “there’s a lot of challenges when it comes to solving unit economics.”¹

The next test is Digit 5. Agility says it has more than $300 million in planned orders tied to 1,000 robots for a single customer, with deliveries targeted for the first half of 2027 and broader availability by year-end. Yet those contracts hinge on performance targets including throughput, uptime and placement accuracy—and the company has not yet publicly demonstrated the new model.²

Agility’s public debut therefore offers a rare market benchmark: real deployments may distinguish it from richly valued private peers, but investors will now price the gap between a robot that works today and a business that can scale tomorrow.¹