\n<\/p>\n
Eric Wu built and ran Opendoor, one of the more ambitious real estate startups of the last decade, before stepping away in 2022 after fast-rising interest rates abruptly slowed down home sales. He spent a year resetting \u2014 he\u2019d been running the company for eight years at that point \u2014 and could have easily jumped into investing when he felt done with his hiatus. But like a lot of founders, he\u2019s so convinced that AI will be the defining tech platform of his lifetime that he more recently decided instead to dive back into company building. As he told me during a call earlier this summer, \u201cI knew if I looked back in 10 years and didn\u2019t do something related to it, I\u2019d probably regret that.\u201d<\/p>\n
The opportunity Wu is chasing \u2014 building AI copilots for construction workers and other field laborers, something he describes as a hands-free expert coach for the people physically building things \u2014 isn\u2019t exactly a secret. The construction industry is short workers by a wide margin. The trade group Associated Builders and Contractors has said roughly 349,000 additional workers<\/a> would be needed this year just to keep pace with construction demand, a challenge that looks to worsen with workers getting older<\/a>, workers getting shipped out of the United States<\/a> owing to more aggressive U.S. immigration enforcement, and also the growing number of major projects being planned, specifically data centers.<\/p>\n We\u2019ve all heard now \u2014 from the entire AI industry \u2014 about the giant server farms that the AI boom demands. Those projects have grown enormous, and staffing demand has grown with them. Where a large data center campus once needed something like 750 workers at its peak, the biggest projects now require 4,000 to 5,000 people. (Meta\u2019s Hyperion campus in Richland Parish, Louisiana will reportedly require roughly 5,000 construction workers<\/a>, and OpenAI\u2019s Stargate site in Abilene, Texas has reported involved 6,400 workers<\/a>.) Kelly, the global staffing company, has said that 90% of data center operators<\/a> now name staffing shortages as a critical constraint on their ability to build or expand.<\/p>\n While that staffing shortage gets discussed far less than the capital and energy requirements associated with these enormous projects, Wu\u2019s new company, called NavigateAI<\/a>, is largely focused on building up that people layer. <\/p>\n The company officially launched in late May with $25 million in seed funding at a $225 million post-money valuation led by Elad Gil, with participation from Khosla Ventures, Fifth Wall, real estate giant Lennar, Tishman Speyer, electrical contractor Helix Electric, and a roster of angels including Tony Xu of DoorDash, Apoorva Mehta of Instacart, and Coinbase CEO Brian Armstrong. <\/p>\n None are particularly surprising, given Wu\u2019s connections to the real estate industry, as well as to Silicon Valley bigs. Gil, for example, was an investor in Opendoor, and Keith Rabois of Khosla Ventures co-founded Opendoor. Khosla Ventures founder Vinod Khosla has also been outspoken in recent years about the dozens of startups in the firm\u2019s portfolio that are building around AI \u201cworkers\u201d of various stripes, whether oncologists, chip designers, or construction workers.<\/p>\n Wu\u2019s core product runs on smartphones and, in hands-free mode, through Meta\u2019s AI glasses. The idea is for a construction worker to point the camera at what he or she is building and ask, in plain language, whether it\u2019s installed correctly, whether the torque is right, whether it meets code, and so forth. Wu says that NavigateAI can pull up building specs, manufacturer manuals, and company policy in real time. He also says the hands-free experience is measurably superior (you don\u2019t want to be looking at a phone when you\u2019re on a job site) and that, in fact, the company is working with Meta to get the glasses safety-certified for environments where protective eyewear is required. <\/p>\n NavigateAI is also partnering with AIM, a Meta-backed fiber installation trade school that guarantees job placement to graduates, giving the company a channel to reach workers before they ever set foot on a job site.<\/p>\n Getting workers comfortable with AI-assisted work during training matters a lot, apparently. Wu says adoption curves split sharply between younger workers, who he says embrace the product, and 30-year journeymen, who trust their own instincts and aren\u2019t exactly lining up to strap a computer to their face.<\/p>\n On the business model, the company started with a token-plus-margin pricing structure \u2014 akin to usage-based SaaS \u2014 but it has migrated its newer contracts to a share of value created. For example, if NavigateAI helps a builder reduce the all-in cost of a home from $300,000 to $280,000, the company captures roughly 20% of that $20,000 savings. Wu told me Lennar \u2014 one of the country\u2019s largest home construction companies and another of NavigateAI\u2019s investors \u2014 spends roughly $9 billion a year on labor, installation, and construction, so even a 5% to 10% improvement would represent hundreds of millions of dollars in potential value.<\/p>\n The longer-term play, which Wu is candid about, is the data. Every job completed with NavigateAI generates labeled egocentric video of field workers building and maintaining physical things correctly and incorrectly, and that\u2019s a dataset that Wu believes will eventually be worth as much to robotics companies as the software business itself is worth to Navigate\u2019s construction clients.<\/p>\n There are, of course, real challenges. Value-based pricing can create an attribution dilemma , as Wu openly acknowledges. Proving that a home was built faster because of NavigateAI and not because of sunny weather, or the particular crew on the job, or the availability of materials, requires A\/B testing across divisions and is approximate by his own admission. You could imagine a client dispute over savings attribution getting complicated fast, even if that client is also an investor in NavigateAI.<\/p>\n That resistance from experienced workers would also seem to be a pretty serious problem. The veteran journeyman is whose industry knowledge would most make NavigateAI\u2019s product smarter, and no trade school can fully replace that know-how. Then there\u2019s safety liability. If NavigateAI\u2019s software clears a connection that later fails, what happens? Defect liability is a notoriously litigious area, and it\u2019s not yet clear how these issues will be handled as they invariably arise.<\/p>\n There\u2019s also, as ever, the competitive question. When we talk, Wu mentions that the most common current alternative is a worker Googling something or asking ChatGPT, and that NavigateAI can go well beyond that. But all the big LLM companies have the model capabilities and, in Meta\u2019s case, the hardware distribution, too. As unlikely as it is, they could spin up their own businesses. Of course, the more likely threat is a similar player. NavigateAI\u2019s defensibility rests on workflow integrations and proprietary data that take years to accumulate. It may have a window right now to get ahead of would-be rivals, but it\u2019s not limitless.<\/p>\n On the flip side, in Silicon Valley, network matters sometimes as much as the product, and the combination of Wu, Gil, Khosla Ventures, and Lennar, among others, functions as strong signal. And either way, Wu doesn\u2019t seem inclined to worry right now about competitors. He just seems excited to be building something new, at a time when not building would feel like a mistake to him.<\/p>\n Underscoring that point, he doesn\u2019t have a board yet, and he says he is \u201cgoing to try to go as long as I can without one,\u201d so he can stay focused on customers instead of governance. You can draw a line between that observation and his time running Opendoor, which went public through a special purpose acquisition company back in late 2020. Being a public company CEO made the parts of the job he wanted to spend his time on harder to do, forcing a constant trade-off between building product and managing a board and shareholders. For now, it\u2019s clearly a trade-off he doesn\u2019t miss.<\/p>\n<\/div>\n When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/em><\/p>\n