Construction Labor Startup Skillit Closes $8.5 Million Seed Extension

The raise bucks proptech funding slowdown


Proptech funding has slowed in 2023, but Skillit, a data-driven recruiting platform for skilled full-time construction labor, is bucking that trend. The startup announced Thursday that it has secured $8.5 million in additional seed-round funding.

The latest funding is in addition to Manhattan-based skillit’s $5.1 seed round in January, and brings the company’s total funding to $13.6 million.

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The funding was co-led by San Francisco Bay Area-based venture capital firm Bow Capital and MetaProp, a proptech VC headquartered in Manhattan, with participation from existing investor Building Ventures in Boston.

Skillit’s platform seeks to provide ENR contractors nationwide with better control of their project life cycle and long-term profitability. It does this by sourcing in-house skilled workers for every trade, including carpenters, electricians, welders and heavy equipment operators.

Despite a challenging macroeconomic landscape, construction presents a unique labor demand that has added to Skillit’s growth, attracting additional investment, said Fraser Patterson, founder and CEO at Skillit.

“There’s still extremely long backlogs in construction,” said Patterson. “If you have a project backlog and you’ve been operating under a chronic labor shortage year after year, then you’re already behind. So the appetite for Skillit hasn’t waned at all. In fact, we’re giving our customers access to not only a radically smarter, more efficient way to hire craft labor, but we’re also providing them with intelligence that they currently don’t have, because this industry has never built the necessary digital infrastructure.”

Such demand has been a boon for Skillit, which plans to expand this year to between 25 and 30 full-time employees, up from nine, said Patterson.

“We raised our seed round just six months ago and since then we’ve seen tremendous growth in all our key metrics, with revenue growing 200 percent month-over-month,” he said. “The majority of the top ENR contractors are in our pipeline, and we also have strong demand from the mid-market.”

What has become a chronic labor shortage in the U.S. construction market can be aided by Skillit, which is a type of “LinkedIn for craft recruitment,” said Patterson.

Skillit taxonomizes and assesses everything from skills and experience to professional goals and preferences in order to generate data-rich worker profiles that make it easy to identify, hire and retain talent. The company claims that its data-driven approach has already resulted in materially more interview requests, offers acceptance rates that are 1.7 times the industry average, and retention rates that are nearly double.

“We’ve quite literally taken the trades and developed a taxonomy of skills,” Patterson said. “It’s  an accurate, structured data set on an individual worker’s skills. On top of that, there’s their career and pay expectations. We essentially structure that through the onboarding of our app, where the worker is able to update their profile. They’re incentivized to do so because it puts them in front of employers that are looking for that information.”

As immigration to the U.S. from Latin America and other regions continues to be a major source of labor for construction, the platform is accessible in multiple languages, added Patterson.

While the construction industry has begun using technology and AI to fulfill some labor functions, Patterson does not see the rise of the latter as solving the industry’s immediate need for skilled workers.

“The problem with most skilled trades is that they are highly dexterous and they’re operating in an ever-changing environment,” said Patterson. “So you fundamentally need a reliable skills data set in order to be able to build any kind of artificial, fully autonomous, artificially intelligent craft worker, or, if you will, a craft robot.”

Creating AI-powered robots for construction is a challenge because the machines rely on large language models composed of massive amounts of publicly available documents, social media posts, research and other data — which, unlike the media, banking or health care industries as examples, is not as available in the built world, said Patterson.

“That intelligence has not really been focused on the craft laborers, carpenters, electricians and plumbers these last few decades, so that data is nonexistent,” he said. “The other piece is that in order for a language model to get smarter and for AI to essentially use it and be reliable, it needs to be in an industry that actually is digitally native and continues to produce data. We’re nowhere near that in the field of construction. So this idea that there would be a full replacement of labor is highly unlikely.”

Philip Russo can be reached at