The expansion of solar energy is one of the most significant developments on Earth today. Globally, efforts are underway by companies and nations to utilize solar power and battery storage to gain energy independence and mitigate climate change impacts.
However, this expansion faces a labor market hurdle: a shortage of skilled workers to meet the rising demand for solar installation. While robots offer a potential solution, they have traditionally struggled in unpredictable settings. Recent advancements in AI models may have altered this scenario.
This is the core concept behind Gritt, a start-up established by Carnegie Mellon-trained roboticists, CEO Puneet Puri and CTO Vishal Dugar. The company emerged from stealth mode on Tuesday morning, announcing a $26 million Series A funding round led by Obvious Ventures, with contributions from Union Square Ventures and Active Impact Investment. This brings Gritt’s total funding to $34 million, including a prior seed round supported by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures. The startup aims to create an intelligent system to “help civilization build infrastructure faster,” according to Puri.
“Our belief is that to truly accelerate construction,” Puri tells JS, “we need intelligence that can operate in outdoor, chaotic construction environments, and it must be adaptable enough to function across diverse settings.”
Instead of designing its own robots, Gritt utilizes off-the-shelf hardware—currently rented skidders and robotic arms from companies like Kawasaki—to develop platforms managed by its AI models. The initial task of its systems is to unload large, glass solar panels, carry them to metal frames for installation, and position them with sub-millimeter precision for workers to secure.
“There are individuals who built rockets with limitless budgets for the smallest parts, and then there are those who excel in scaling challenging jobs,” said Andrew Beebe, partner at Obvious Ventures, who led Gritt’s Series A round. “This team belongs to the latter category, with the necessary technical skills, AI expertise, and machine vision capabilities to succeed.”
Gritt has two systems currently deployed in the field, gathering data to enhance their performance. Puri notes that an eight-person crew traditionally installs 800 panels daily, but with Gritt’s systems, they can install between 3,000 and 4,000 panels per day.
The company now reports it is contracted to assist in installing 2.8 gigawatts of solar panels over the next 18 months, with its clientele including three of the top 10 US power construction companies. Gritt aims to operate 48 systems within the next six months.
JS spoke to a Gritt customer who wished to remain anonymous for competitive reasons. He expressed enthusiasm for the system’s ability to enhance his operations, expecting it to simplify work at remote locations where attracting workers is challenging, and reduce injuries as workers will no longer need to lift 100-pound panels overhead.
Gritt faces competition from companies developing their own panel-installing robots, such as Luminous Robotics, Cosmic, and China’s Trinabot. These companies focus on building custom hardware, contrasting with Gritt’s approach of using existing vehicles and arms, a difference that could influence who expands faster with a more cost-effective model as demand increases.
Gritt plans to incorporate additional manipulation tasks into its system, such as fastening solar panels, drilling posts, and even constructing the racks they rest on. In the long term, it aims to tackle other common, labor-intensive construction tasks, like tying rebar before pouring concrete.
The rise of new AI models has primarily enabled the startup to pursue this vision, according to the founders.
“Creating a system for a single solution was feasible to some extent five years ago,” Puri explained, “but AI now allows for generalization—using the same pipeline across different tasks.” He cited the example of training the system to stack cinder blocks, which took weeks, while a similar demo with rebar tying was accomplished in just a day using the same software.
However, developing new tasks is just the start of Gritt’s vision. The founders believe their systems, equipped with sensors and intelligence, can do more than just install panels; they can enhance management and decision-making. For example, they envision the system detecting an open trench as a storm approaches, prompting workers to cover it before rain causes damage or alerting them to missing inventory.
“Gritt now represents a layer of physical AI, performing dexterous, labor-intensive tasks, while also aiding in on-site decision-making,” Puri said.
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