America Rebuilds Its Industrial Base. Emanate Builds The Growth Engine

Aerial view of a manufacturing facility

Kiara Nirghin

Doing sales for an industrial company is a tough job. In addition to all of the usual roles a sales representative has to play – outbound outreach, inbound inquiry management, spending time with customers, the usual administrative duties – they also need to have deep expertise in the materials or services they are selling, be up to minute on the latest tariffs and regulations, and calculate complex numbers in order to provide price quotes. Emanate, a startup based in the Bay Area, is aiming to change that, by providing an AI platform that handles much of the work done by these reps, freeing them up to focus on relationships and communication with customers.

Industrial materials and distribution companies, a five trillion dollar market, has been seen as slow or behind the times, but founder Kiara Nirghin believes that this technology will lead to a great leveling across industries. “Now the companies that have historically been considered slow to adopt things now just [have] equal footing to every net new thing,” she says, “And that is some of the largest leveling that will ever exist. I actually think that you'll never consider these companies to be slow-moving ever, because the things that have held them back — like engineering capacity or being able to scale the commercial side — won't exist anymore.”

Nirghin’s thesis has found support from powerful VC’s, including Andreessen Horowitz. "Most AI in the enterprise is sold for cost-cutting. Emanate stood out by building AI that drives top line growth, and focusing on a massive but overlooked industrial materials market that is the backbone of the modern economy," says Jonathan Lai, General Partner at Andreessen Horowitz, one of the startup’s first investors. A newly closed oversubscribed round also includes funding from M13, alongside firms led by a former Khosla Ventures GP and the first investor in Groq.

Of course, there are plenty of AI-powered sales tools in the market already, but Nirghin points out that they’re not equipped to handle the level of complexity that industrial companies often deal with. “In the industry, the products are deeply complex,” she says. “You have to understand technical specs, grades, and processing requirements. These are actually genuinely mathematical decisions in how materials are priced, processed, or how they get into customers' hands. No horizontal AI can actually do this.”

Emanate also focused on building a harness around its models, which is built for industrial specifics: multi-week quoting cycles, mill-grade specifications, remnant inventory tracking. "Our agent harnesses are mathematical in nature. The agent computes against the customer’s live system data, checks itself, checks itself again, and humans supervise the work.” says Nirghin. “We make sure that there's a self-learning loop involved. With a really good agent harness, I've never seen hallucinations.

The market Nirghin is focusing on is both underserved and poised for rapid growth, as the US Government has named re-industrialization as a top priority in the coming years. Until recently, many of these companies have run on old-school practices like spreadsheets and phone calls, and longtime employees who retire or leave generally take all their institutional knowledge with them. Now, AI will give them the ability to scale up and retain and deploy that knowledge, competing with other markets.

"When people in Silicon Valley think about these industries, they always say, it's a very old industry that's never taken up technology,” says Nirghin. “And that is not the case... Have you ever thought about the amount of innovation that had to go into getting the steel pipe that takes the water into our tap to get there? That is way more innovation than the email."

Nirghin, is a Stanford alum, Thiel Fellow, and Google Grand Prize winner for her AI research. She has been named to TIME Magazine's Most Influential list. Emanate is a team of computer scientists and AI engineers from Stanford, Berkeley, MIT, Google, Meta and NASA.

As AI evolves, its ability to handle complex and industry-specific tasks means a leveling of the playing field between industries. Frontier models will be available to be used by everyone from cutting-edge startups in Silicon Valley to industrial firms in the midwest, and the rising tide will likely lift all boats. Reindustrialization is rebuilding what America makes; the unsolved problem is how it gets sold.