Meet the robots being trained to build solar farms faster than any human crew
A startup called Gritt says its AI-controlled machines can help an eight-person crew install four times as many solar panels in a day. It just raised $34 million to prove it.
Key points
- Gritt, a robotics startup founded by two Carnegie Mellon University engineers, exited stealth on Tuesday with a $26 million Series A funding round.
- Total funding now stands at $34 million, with Obvious Ventures leading the latest round alongside Union Square Ventures and Active Impact Investment.
- A typical eight-person crew installs around 800 solar panels per day; working alongside Gritt's systems, the same crew can install 3,000 to 4,000 panels per day.
- Gritt is contracted to help install 2.8 gigawatts of solar capacity over the next 18 months.
- Three of the top ten US power construction companies are already Gritt customers.
Solar panels are going up everywhere. Governments and energy companies are racing to build new solar farms, and demand for skilled installation workers is outpacing the supply of people willing, or able, to do the job.
Gritt thinks robots can fill that gap. It's not the only company betting on that idea: we covered Maximo's AI-guided solar robots on 17 July and Xpanner's panel-lifting arm on 16 July, and Gritt's announcement makes three solar-installation robotics stories in as many days on this beat.
The startup, co-founded by CEO Puneet Puri and CTO Vishal Dugar, both Carnegie Mellon-trained, builds AI-controlled systems that handle the most physically punishing parts of a solar installation. Right now that means one main job: picking up heavy glass panels, carrying them across rough ground, and positioning them on metal frames with sub-millimetre accuracy so human workers can bolt them in place.
Workers lift those panels, which weigh roughly 100 pounds each, overhead, repeatedly, all day. Injuries are common, and getting crews to remote sites is genuinely hard. One Gritt customer, speaking to TechCrunch AI but not willing to be named publicly, said the system should make remote sites more workable and reduce the number of injuries on his jobs.
Gritt doesn't build its own robots from scratch. It rents off-the-shelf hardware, wheeled skid-steer loaders and robotic arms made by companies such as Kawasaki, and controls them with its own AI software. That software is the product. Think of it like an experienced driver who can take the wheel of almost any vehicle, rather than a manufacturer who builds one machine and hopes it fits every road.
Does this put construction workers out of a job?
Not in the near term. The system works alongside existing crews, not instead of them. Workers still fasten the panels; the robots handle the carrying and positioning. The jump from 800 panels a day to 3,000 to 4,000 means more sites get built with the same number of people.
Gritt has two systems in the field right now and wants 48 deployed within six months. Rivals Luminous Robotics, Cosmic and Trinabot of China are all building similar machines, but those companies are developing their own hardware. Gritt's bet is that focusing purely on software and renting existing equipment lets it grow faster at lower cost.
Longer term, Gritt wants its systems to fasten panels, drill posts and build the racks panels sit on, eventually branching into other heavy tasks like tying steel reinforcing bars before concrete is poured. Training the system to stack cinder blocks took weeks; using the same software, training it to handle rebar took just one day. That speed, the founders say, is what the latest generation of AI models made possible.
For anyone watching the clean-energy build-out, the software-only model is the real story here. Hardware companies can be copied; a proprietary AI layer that learns new construction tasks in a day is harder to displace.
