Story
Nov 9, 2026
Agility Reaches Wall Street, but Digit Still Has to Prove It Pays
Agility Robotics has taken its warehouse humanoid public with a $465 million capital raise and real deployments to show. Investors must now decide whether Digit’s early lead can overcome steep losses, high costs and a crowded race.
Agility Robotics, spun out of Oregon State University in 2015, spent years pursuing a less glamorous path than many humanoid rivals: getting a two-legged machine to perform repetitive industrial work. Its Digit robots now operate at nine customer facilities, including Amazon, Toyota and GXO, and have moved more than 100,000 totes at one GXO site.1
That field experience became the foundation of Peggy Johnson’s pitch as Agility went public Thursday through a SPAC merger, raising about $465 million to increase Digit production and deployment. Johnson’s message is that warehouses and factories do not need robot spectacle; they need help with jobs employers struggle to fill. “This is a real business problem right now, and we can fill that need that companies have for automation,” she said.2
The market offered an immediate reality check. Trading under AGLT, Agility closed Friday at $9.90, nearly 14% below its Thursday close. The selloff sharpened the central tension behind the listing: Agility has a robot in the field, but not yet a proven financial engine.
Its filings show $1.8 million in revenue and a $138.1 million net loss last year. Another account of the company’s more recent performance put revenue at just $174,000 in the first half of 2026 against a $362 million loss. Agility says it has more than $300 million in planned Digit 5 contracts, but the new model must still meet targets for throughput, uptime and placement accuracy before those deals can scale.1
Johnson is betting volume will close the gap: Digit 5’s materials cost is projected to fall from $150,000 initially to $30,000 at annual production of 10,000 units. Skeptics see a large if. The robot must work reliably, reduce maintenance and recharge downtime, and justify an estimated $500,000 on-site proof of concept for prospective customers.
Competition leaves little room for delay. Figure AI, Apptronik and Tesla are all advancing their own humanoid programmes. Agility’s advantage is its operational data—65,000 hours gathered in real facilities. Its vulnerability is the same one confronting the sector: a promising machine is not yet proof that the economics work.