From Bankruptcy Prediction to Public Listing
Almost exactly a year ago, Figure AI CEO Brett Adcock responded to some gentle social media taunting from rival robotics company Agility with a bold prediction: "You'll be bankrupt in <12 months."
Instead, Agility is going public through a reverse merger that will see it become a publicly traded company and raise $465 million in new capital from retail investors and a tranche of private funding. The transaction will take place through a special purpose acquisition company, or SPAC.
"You don't see a lot of dancing robots or backflipping robots from Agility," CEO Peggy Johnson told TechCrunch ahead of the company's market debut. "We stuck to our strategy, which [are] these manual, very repetitive jobs, that it's hard to find humans to do."
A Decade in the Making
Agility predates the recent boom in physical AI investment. The company was spun out of Oregon State University in 2015 by a group of researchers who made headway in figuring out how to get a robot to walk safely on two legs. The company has focused on deploying a handful of its Digit robots in industrial settings with nine different customers, including Schaeffler, GXO, Toyota Motor Manufacturing Canada, and Mercado Libre. Digits are generally used to move heavy totes, including more than 100,000 of them at a GXO logistics facility.
Compared to humanoid robots built by Figure, Tesla, 1X, or Boston Dynamics, Agility's Digit can seem plodding, but the robot is actually doing real work — and earning money — albeit just $174,000 in the first six months of 2026, and mostly from related parties. The company lost $362 million in the same time period, which means the clock is ticking for it to successfully deploy its infusion of new capital.
Digit 5 and the Road to Commercial Scale
The good news is that Agility has $300 million in planned contracts from 30 customers for its new generation of robot, Digit 5. The new model can safely operate around humans, not just in an isolated work cell like its previous model (and indeed most humanoid robots). That deal was "one of the driving factors" behind the decision to take the company public, Johnson said, but she could not yet reveal who the customers are or say whether they are investors.
To close the deals, Johnson said that Digit 5 will have to hit undisclosed targets along several metrics, including throughput, uptime, and accuracy of placement. The company has yet to show off the prototypes of Digit 5, but Johnson said they will be demonstrated at CES 2027 and widely available at the end of that year.
The Unit Economics Bet
The company's pitch is that a robot can save $100,000 a year for companies under a robot-as-a-service model — and even more if the customer purchases the robot outright. Whether those unit economics work out in the end will depend on Digit 5's capabilities, both in terms of task accuracy and how long it can work without pauses for recharging or maintenance.
Johnson gave the example of a single person lifting a 50-pound object — an informal threshold some workplaces use to avoid injury. "Digit can do that over and over and over," she said. "You don't want to give a human that job. You want to give that to the robot."
Two Key Questions for Investors
Agility faces two key questions: How quickly can it find new customers for Digit 5, and how quickly can it improve on the robot's capabilities? Prospective customers need to spend $500,000 for Agility to do an on-site proof of concept before a deployment is fully scaled up; there were four customers signed up in May 2026. And while Agility can pick up heavy loads and place them with 98% accuracy, it still — like most of today's robots — lacks the ability to do complex manipulation tasks.
It's still not clear how quickly generative AI techniques will unlock the kind of dexterity that could allow robots to handle a wide variety of items. Training systems based on large-scale imitation learning and reinforcement learning are advancing rapidly, but the gap between demo-grade dexterity and reliable, production-grade manipulation remains wide.
The Bottom Line
For investors weighing whether to buy in, Agility offers something rare in the humanoid robot space: a company with real deployments, real customers, and a clear — if narrow — commercial strategy. But the risks are equally real: steep losses, modest revenue, unproven next-generation hardware, and a market that remains years away from the kind of general-purpose dexterity that has fueled so much hype. Agility's public debut will be a bellwether not just for the company, but for the entire physical AI sector heading into 2027.
via TechCrunch