Roughly 25% of the companies we’ve looked at this year have been robotics companies. Nearly all of them, from pre-seed to Series A, raise venture equity and spend a big chunk of it on hardware, including the fleets they deploy to customers.
In most industries that would be strange. Trucking companies don’t sell equity to buy trucks, and farmers don’t sell stakes in the farm to buy tractors. Machines that earn contracted revenue get bought with debt, because a lender can underwrite the cash flows and take the machine back if they stop. Robotics startups are funding exactly that kind of asset with the most expensive capital they’ll ever raise.
Equity is buying the fleet
A commercial robot costs $20-100K. Under a signed service or lease contract, it earns a few thousand dollars a month and pays for itself in 12-18 months. Land a customer for 50 units and you need millions in hardware before revenue arrives. Most startups can only fund that with another equity round, taking permanent dilution to cover an 18-month gap. Robotics startups raised $18.8B globally by June, more than in all of 2025, and a lot of it is buying hardware. One of our portfolio companies told us they’d put $20M into their fleet tomorrow if they could get it, but raising it as equity at their stage isn’t realistic.
In theory, there are three ways to fund this without equity:
Equipment financing covers the machines used to build robots, like CNC machines, which have deep resale markets.
Fleet financing lends against robots a startup deploys itself under a signed contract. The lender is repaid from the contract and can repossess the robots if that fails.
Customer financing does the most. A lender pays the startup upfront and the customer repays over its contract. The startup gets cash on delivery to buy its next batch of parts, and the credit risk moves to the customer, who is often a much bigger company.
The parts themselves are the hardest to lend against. Motors and gears get customized, built into prototypes, or used up in R&D, and their resale value drops fast once that happens.
Why nobody lends
Banks want years of operating history and profits. Equipment lessors want two years of financials, which is unrealistic for a seed-stage company. Venture debt usually starts at Series B, comes with warrants, and takes a lien on the whole company, so the founder pledges everything to finance one fleet.
Bank capital rules make it worse, and GPUs show how. Under Basel III, a loan repaid from a specific asset’s cash flows counts as “object finance” and gets slotted into preset risk buckets that punish anything unproven. So banks lend to private credit funds instead, and the funds lend against the GPUs at higher rates.
USD.AI was built for that gap. It takes stablecoin deposits and lends them against tokenized GPUs. Its largest loan grew from $620K in July 2025 to $98.1M this June, with $202M deployed and ~$30M of annualized revenue in Q2. Deposits went the other way, from $650M+ at its January token launch to ~$225M by August. On-chain capital is easy to attract. Origination is the business.
Insurance is moving faster
Corgi is an AI-native insurance carrier for startups. Instead of acting as a broker, it writes and prices policies itself, using company data rather than long application forms. It was founded in 2024, reported $40M of annualized revenue at its January Series A, and reportedly raised at a $4B valuation in July, tracking toward a $450M run rate by year end. The lesson is that a carrier underwriting from data can win the categories incumbents handle badly, and robots are one of them.
Boop is already there. It sells per-robot insurance to companies deploying robots and includes a black-box recorder that settles claims on evidence. It argues standard liability policies likely exclude autonomous failures. Boop started out pitching insurance for household humanoids, and its pivot to commercial fleets shows where the demand is.
The missing piece
Robotics operators need financing and insurance at the same time, for the same robots. Both are underwritten on the same data: what the robot is, where it works, how much it’s used, and who’s paying for it.
Other machine industries solved this at the point of sale. When you buy a car, the dealer offers you a loan and insurance at the same desk. GM started its own lender, GMAC, in 1919 because customers couldn’t buy cars they couldn’t finance. John Deere’s lending arm holds ~$49B of loans today.
Robotics doesn’t have this yet. Robot makers are young and don’t lend to their customers. We think a startup will fill that gap by offering financing and insurance right where robots are bought.
That’s where crypto comes in. Stablecoin holders want real yield, and short, contract-backed loans against working robots fit that well. But as USD.AI shows, capital isn’t the bottleneck. The hard part is originating good loans.
We’ve been thinking about this all year and recently met founders already doing that work. If you’re building credit or insurance for the physical economy, or you’re a robotics founder spending your seed round on a fleet, we’d like to talk.
@Anthony Avedissian - I’ve been trying to get your attention on X (at jfrnrd). Would love to talk about an idea I have. DM’d you on LinkedIn! :)