Solar build-out faces labor shortage
The global push to deploy solar energy and batteries is one of the most significant efforts underway to combat climate change and achieve energy independence. But this build-out is hitting a bottleneck: there are not enough workers to meet the growing demand for installation.
Robots could help fill the gap, but industrial robots have historically struggled in unstructured outdoor environments. Recent advances in AI models may have changed that, opening the door for automation on construction sites.
Gritt's approach: off-the-shelf hardware, AI smarts
Gritt, a startup founded by Carnegie Mellon-trained roboticists Puneet Puri and Vishal Dugar, is betting on that shift. The company exited stealth on Tuesday with a $26 million Series A round led by Obvious Ventures, with participation from Union Square Ventures and Active Impact Investment. That brings its total funding to $34 million, following a seed round backed by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures.
Puri described the company's mission as building an intelligent system to "help civilization build infrastructure faster."
"Our thesis is that if we truly want to speed up construction, you need an intelligence which can work in the outdoor, chaotic environments of these construction sites, and it has to be generalizable enough that it can work in these varied environments," Puri told TechCrunch.
Rather than designing and manufacturing its own robots from scratch, Gritt uses off-the-shelf hardware. So far, it has rented skidders and robotic arms from companies like Kawasaki. Its AI models control these platforms. 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.
Andrew Beebe, the Obvious Ventures partner who led the Series A round, praised the founders' approach.
"There are people who used to build rockets that went into space and had infinite budget for the smallest little part, and then there are people who know what it means to get into dirty, dull, and dangerous jobs and scale them like mad," Beebe said. "These guys are in the second camp, and that's a special kind of entrepreneur that has the technical chops, the AI, and the machine vision skills to make it work."
Field deployments and productivity gains
Gritt currently has two systems deployed in the field, collecting data to improve their performance. Puri said a typical eight-person crew can install 800 panels per day. The same crew working with Gritt's systems can install 3,000 to 4,000 panels each day.
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The company says it is contracted to help install 2.8 gigawatts of solar panels over the next 18 months. Its customers include three of the top 10 U.S. power construction companies. Gritt hopes to have 48 of its systems operating within the next six months.
TechCrunch spoke to one Gritt customer who declined to be identified for competitive reasons but was enthusiastic about the system's impact. He expects it will make work easier at remote sites where attracting workers is difficult, and anticipates fewer injuries since workers will no longer have to repeatedly lift 100-pound panels overhead.
Competition and differentiation
Gritt competes with companies like Luminous Robotics, Cosmic, and China's Trinabot, all of which build their own panel-installing robots. Gritt's focus on off-the-shelf vehicles and arms rather than custom hardware could give it an advantage in scaling faster and maintaining a leaner cost structure as demand grows.
The startup plans to add new manipulation tasks to its system, such as fastening solar panels, drilling posts, and building the racks they sit on. Longer term, it wants to move into other labor-intensive construction tasks like tying rebar before concrete is poured.
AI models enable generalization
The founders attribute their progress to advances in AI models.
"Making a system for one solution was still possible to some extent five years ago, right?" Puri said. But AI now makes that work generalizable. The same underlying pipeline can be reused and improved across tasks. He noted that training the system to stack cinder blocks took weeks, while a similar demo with rebar tying took just a day using the same software.
Beyond installation: a layer of physical AI
Gritt's vision extends beyond installing panels. The founders believe the suite of sensors and intelligence its systems bring to worksites can improve management and decision-making. For example, the system might notice a trench is open while a storm approaches and alert workers to cover it before rain damages components, or flag missing inventory.
"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.