Robotics startup Gritt emerged from stealth Tuesday with $32 million in total funding, betting that AI-controlled machines can solve the labor shortage slowing the global solar energy build-out. The company’s systems already help crews install up to 4,000 solar panels per day, a fivefold increase over manual methods.
The $26 million Series A round was led by Obvious Ventures, with Union Square Ventures and Active Impact Investment participating. An earlier seed round backed by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures brought total funding to $32 million. Founded by Carnegie Mellon-trained roboticists Puneet Puri (CEO) and Vishal Dugar (CTO), Gritt is building what Puri calls “an intelligence which can work in the outdoor, chaotic environments of these construction sites.”
Off-the-Shelf Hardware, Custom AI
Unlike competitors building proprietary robots from scratch, Gritt rents off-the-shelf industrial equipment — skidders and robotic arms made by companies like Kawasaki — and controls them with its own AI models. The approach keeps capital costs lean while the software does the heavy lifting. The first task Gritt’s systems handle is unloading large glass solar panels, carrying them to metal frames, and positioning them with sub-millimeter accuracy so workers can fasten them in place.
The productivity gains are significant. A typical eight-person crew installs roughly 800 panels per day. The same crew working alongside Gritt’s systems installs 3,000 to 4,000 panels daily. One customer, who declined to be identified for competitive reasons, said the system should make it easier to operate at remote sites where attracting workers is difficult and should reduce injuries by eliminating the repeated overhead lifting of 100-pound panels.
Scale and Pipeline
Gritt reports it is contracted to help install 2.8 gigawatts of solar panels over the next 18 months, with customers that include three of the top 10 U.S. power construction companies. The startup currently has two systems deployed in the field and aims to operate 48 systems within six months. Each deployed unit collects data that feeds back into improving the AI’s behavior, creating a learning loop that accelerates as the fleet grows.
The construction robotics space is getting crowded. Luminous Robotics, Cosmic, and China’s Trinabot are all building panel-installing machines, though each manufactures its own hardware rather than relying on off-the-shelf platforms. That difference could determine which companies scale fastest as demand for solar installation surges. Gritt’s leaner hardware footprint may let it expand without the manufacturing overhead competitors carry.
From Solar Panels to Construction’s Broader Labor Gap
Solar installation is just the entry point. Gritt plans to add manipulation tasks — fastening panels, drilling posts, building the racks panels sit on — and eventually move into other labor-intensive construction work like tying rebar before concrete pours. The underlying AI pipeline is designed to generalize across tasks. Puri noted that training the system to stack cinder blocks took weeks, while a similar rebar-tying demo took just a day using the same software.
The founders see a larger opportunity beyond physical labor. The sensors and intelligence Gritt’s systems bring to worksites could function as a layer of “physical AI” that also supports site management. A system might notice an open trench before an approaching storm and alert workers to cover it, or flag missing inventory before it delays a project. “Gritt becomes now this layer of physical AI, which is doing this dextrous, labor-intensive task, plus it can help you take decisions on the site,” Puri said.
What Happens Next
Watch whether Gritt can hit its target of 48 deployed systems within six months — that pace will test whether its off-the-shelf hardware strategy scales as fast as the founders claim. The 2.8-gigawatt installation pipeline gives the company roughly 18 months to prove its model at commercial scale. If productivity gains hold across diverse sites and weather conditions, expect the construction automation land grab to intensify, with competitors forced to defend their cost structures against Gritt’s software-first approach. Longer term, the real test is whether Gritt’s AI generalizes beyond solar into rebar tying, rack building, and other tasks — or whether each new application requires fresh engineering that slows expansion.
— David Kim, technology desk, AXO News