Greet sneaks out $34 million for robots to build solar power plants, and then everything else

One of the most important things happening on Earth today is the accumulation of solar energy. Around the world, companies and countries are racing to deploy solar power and batteries to achieve energy independence and reduce the effects of climate change.

However, this construction faces a challenging labor market, with a limited supply of workers to meet the growing demand for installation. Robots could be an answer, but industrial robots have historically struggled in unstructured environments, at least until now. The latest generation of AI models may have changed this equation.

This is the driving idea behind gravela startup founded by two Carnegie Mellon-trained roboticists, CEO Puneet Puri and CTO Vishal Duggar. The company emerged from stealth on Tuesday morning with a $26 million funding round led by Obvious Ventures with participation from Union Square Ventures and Active Impact Investment. This brings its total funding to $34 million, following a previous seed round backed by First Round Capital, Climatectic, Congruent Ventures, and VSC Ventures. The startup is building an intelligent system to “help civilization build infrastructure faster,” Puri said.

“Our hypothesis is that if we really want to speed up the construction process, you need intelligence that can work in the chaotic outdoor environments of these construction sites, and it needs to be generalizable enough to be able to work in these diverse environments,” Puri tells TechCrunch.

Instead of building its own robots from scratch, Gritt uses off-the-shelf hardware — so far, rental snowmobiles and robotic arms made by companies like Kawasaki — to build platforms controlled by its own AI models. The first task their systems handle is unloading the large glass solar panels, carrying them toward the metal frames where they need to be installed, and positioning them on the frames with sub-millimeter precision so workers can install them.

“There are people who used to build rockets that went into space and had an unlimited budget for even the tiniest bit, and there are people who know what it’s like to take dirty, boring, dangerous jobs and scale like crazy,” said Andrew Pape, a partner at Obvious Ventures who led Gritt’s Series A round. “These guys are in the second camp, which is a special kind of entrepreneur who has the technical skills, the artificial intelligence, and the machine vision skills to make it work.”

Gritt has two systems currently deployed in the field, using the data they collect to improve their behavior. A typical crew of eight can install 800 panels a day, but the same crew that works with GREAT Systems can install 3,000 to 4,000 panels a day, Puri says.

Now, the company says it’s contracted to help install 2.8 gigawatts of solar panels in the next 18 months, and that its clients include three of the 10 largest energy builders in the United States. The company hopes to operate 48 of its systems within the next six months.

TechCrunch spoke to one Gritt customer who declined to be identified for competitive reasons, but who was excited about the system’s ability to improve his business. He expects it will be easier to work in remote locations where workers are harder to attract, and he expects a reduction in injuries because workers won’t have to lift 100-pound panels as frequently.

Gritt competes with companies that have their own panel mounting robots, e.g Luminous robots, BeAnd China I got it. These companies build their own hardware, rather than focusing on off-the-shelf vehicles and weapons like Grit, a difference that can make who grows faster and with a leaner cost structure as demand grows.

Gritt wants to add new processing tasks to his system so he can install solar panels, drill poles, and even build the shelves they sit on. In the long term, you also want to move on to other common, labor-intensive construction tasks, such as attaching rebar before pouring concrete over it.

What enabled the startup to pursue this vision? The founders say the main reason behind this is the emergence of new artificial intelligence models.

“Creating a system for a single solution would have still been somewhat possible five years ago, right?” But AI now makes this work generalizable, as the same basic path can be reused and improved across tasks, Puri said. For example, he noted, training the system to stack cinder blocks took weeks, while a similar demonstration of tying rebar took just a day using the same software.

But training for new missions is just the beginning of Griet’s vision. The founders believe the array of sensors and intelligence their systems bring to jobsites can do more than just install panels; It can enhance management and decision making. For example, they imagine their system noticing that a ditch is open during an approaching storm, allowing it to alert workers to cover it before rain damages components, or report missing inventory.

“Gritt now becomes this layer of physical AI, which does this nimble, labor-intensive task, plus it can help you make decisions on site,” Puri said.