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Nov 6, 2026
Agility Hits Nasdaq With Warehouse Proof but a $362 Million Question
Agility argues that working robots and real-world operating data put it ahead of flashier humanoid rivals, while investors must decide whether that head start can overcome steep losses and the still-unproven performance of Digit 5.
Agility Robotics began in 2015 as an Oregon State University spinoff, built around a difficult but fundamental achievement: getting a robot to walk safely on two legs. Rather than chase demonstrations designed for viral appeal, the company put its Digit machines into industrial settings, working with nine customers including GXO, Schaeffler, Toyota Motor Manufacturing Canada and Mercado Libre.1
That strategy has given Agility a claim many humanoid-robot competitors cannot yet make: Digit has moved more than 100,000 heavy totes at a GXO logistics site. Chief executive Peggy Johnson framed the choice bluntly: “You don’t see a lot of dancing robots or backflipping robots from Agility.” The company, she said, concentrated on repetitive manual work that employers struggle to staff.1
The evidence of demand remains modest beside the cost of getting there. In the first six months of 2026, Agility recorded $174,000 in revenue—largely from related parties—while losing $362 million. Its coming Nasdaq listing through a SPAC merger will bring $465 million in fresh capital, buying time but not settling the central question of whether warehouse robotics can become a durable public-market business.1
Next comes Digit 5. Agility says it has $300 million in planned contracts from 30 customers for the new model, which is intended to work safely alongside people rather than inside segregated cells. But those contracts hinge on targets for throughput, uptime and placement accuracy, and the company has not publicly shown the prototypes. A CES 2027 demonstration is planned, followed by wider availability at the end of that year.1
Johnson’s case is that operational data is the moat: Agility has accumulated 65,000 hours from real facilities, data she says speeds training. Skeptics have a more immediate ledger to watch—whether Digit 5 can move beyond 98% placement accuracy and basic tote handling, justify costly proofs of concept, and work long enough without charging or maintenance pauses. Agility may be first among pure-play humanoid makers to reach the stock market; it is not yet first past the economics test.1