EliseAI Raises $350 Million at $4 Billion Valuation in Round Led by a16z and Bessemer

EliseAI has raised $350 million at a $4 billion valuation, nearly doubling its worth in just over a year, the company told Fortune.

Andreessen Horowitz (a16z) and Bessemer Venture Partners co-led the round alongside a new investor, Ontario Teachers' Pension Plan. Existing backers Sapphire Ventures and Navitas Capital also participated. The deal marks the fourth time EliseAI has raised capital from the two VC firms since 2023, and it comes roughly 13 months after the company's $250 million Series E valued it at $2.2 billion.

Nearly all of EliseAI's major existing investors joined the round, which consisted entirely of primary capital. There was no secondary sale for early investors or employees, according to CEO and co-founder Minna Song.

"We're bringing on our existing investors who wanted to co-lead — Andreessen Horowitz and Bessemer Ventures," Song told Fortune in an interview. "They've really been up close and personal with our company over the last year and decided to double down on what we're building."

Asked to explain the valuation surge, Song credited execution rather than a single catalyst. "It's a result of the effort of our whole team. We've really expanded within the industries that we serve, housing and healthcare. We've delivered more and more products for them — increased the value that we're bringing to our customers, and increased our penetration in the markets. Investors are seeing that."

The new financing will fund product development and expand EliseAI's engineering, deployment, and sales teams across North America. The company plans to open a second engineering hub in San Francisco, alongside its New York headquarters — a 109,000-square-foot office in Manhattan's former Tiffany & Co. building on Fifth Avenue, which it moved into this summer.

Betting on industries tech forgot

EliseAI's pitch has always run counter to Silicon Valley convention. Instead of chasing horizontal AI tools for knowledge workers, the company targeted two of the least glamorous, most heavily regulated corners of the economy: property management and healthcare administration. Thin margins and phone-based bureaucracy have resisted automation in both sectors for decades.

"The industries where AI matters most are still not the ones getting the most attention," said Song. "Housing has enormous problems to solve, and we've grown by going deeper with our customers until we solve them at the root."

Song took a job at a real estate firm before writing any code — a "research phase," as she described it — to discover what drove high costs and operational inefficiency. "We were really just looking for: what is the one bottleneck that's happening in the industry?" she said. "If we could solve just that one bottleneck, it would make a difference." Over time, that scope expanded to most of the operational friction in leasing and resident services.

She argues the same logic applies across the economy's overlooked sectors. "Now people are starting to realize we can go back to some of those industries that don't seem like the new, sexy, industry-creating thing, but they still have a ton of problems," Song said. "It's time to go solve the important things that have largely been unchanged for decades."

The underlying data back her affordability framing. Renter households earning under $30,000 a year face the steepest housing cost burdens in the country: 66.5% describe the burden as "severe," spending more than half their income on rent, according to a Congressional Research Service analysis of Census data. The median renter in the lowest income bracket pays 56% of monthly income toward rent alone, per Federal Reserve research.

Landlords face pressure from the other direction. National multifamily operating costs rose 9.3% in a single year through mid-2023, adding more than $800 per unit annually, driven largely by an 18.8% spike in insurance costs, according to Yardi data cited by the Pension Real Estate Association. A separate Federal Reserve study found multifamily insurance costs rose 75% in real terms between 2019 and 2024 — from $39 to $68 per unit per month — with landlords absorbing roughly three-quarters of that increase through lower profits rather than passing it to tenants.

Healthcare shows a similar squeeze. 41% of U.S. adults carry some form of medical debt, including debt owed to credit cards, collections agencies, or family members, according to KFF polling.

"You can't make housing meaningfully cheaper without making it cheaper to operate," Song said. "Making care more affordable means making it less expensive to deliver… it really all fundamentally has to be cheaper to deliver. That's where AI can have a very tangible impact."

The approach has scaled. EliseAI's software automates leasing, resident services, maintenance requests, and lease renewals for landlords. The company says its platform now powers roughly one in six apartments in the United States, and more than 30 million Americans have interacted with it. EliseAI surpassed $200 million in annual recurring revenue in June, marking its fifth consecutive year of doubling revenue on a year-over-year basis.

From Apollo to healthcare

Earlier this month, EliseAI launched Apollo, a single AI agent designed to complete any task across the Elise platform rather than handle one narrow function.

Song described Apollo as part of a broader shift in enterprise software. "Historically, software has been reactive, and the human has to navigate all the software and tell it what to do. AI is a new application layer — instead of having people navigate dozens of systems and workflows, the AI is just doing it for them."

Apollo "recognizes what needs to happen" and "takes actions within the permissions that it's given," she said, while humans remain involved for anything requiring judgment. "The humans don't disappear. They're still there when something requires judgment or nuance or the human touch. But the AI is handling more and more of the operations and just knows when to bring the person in."

Song stressed the safeguards: "anything that ends in a binding decision such as approving or denying an application, sending a formal notice or signing off on a lease term, tasks like that still go through a person." Fair housing calls work the same way — Apollo drafts a response, flags the relevant policy, and queues it up, "but it doesn't get the final say. And when it doesn't have enough information to act with confidence, it says so instead of guessing. That's been a requirement since day one."

The company is running the same playbook in healthcare. A dedicated EliseAI healthcare business serves specialty physician groups, automating the full patient journey — inbound calls through referrals, scheduling, insurance verification, chart preparation, and follow-up.

Much of the volume runs through phone calls. EliseAI now handles roughly 5 million calls a month across its housing and healthcare businesses combined, Song said. The company has also been working closely with OpenAI, testing new voice capabilities at scale. "We're one of the largest AI deployments at scale… it's really great because they're working a lot on voice, and we can test their new things quickly. It's a win-win for both parties."

"EliseAI has spent years building inside the day-to-day complexity of housing," said Sameer Dholakia, a partner at Bessemer Venture Partners who is joining EliseAI's board with this round. "The company combines exceptional AI research and engineering with a detailed understanding of how properties operate. That depth has produced measurable results for their customers, leading to deep customer love."

What to watch

Despite the valuation jump, Song was noncommittal on any path to a public offering. "We're trying to focus on building the best business we possibly can," she said. "I don't think we have any specific timelines or definitive outcomes … we want to make a great outcome for everyone and all stakeholders."

Housing and healthcare together account for more than 40% of what the average American household spends — a figure EliseAI leans on to argue that solving operational friction in these sectors carries outsized economic weight compared with productivity tools aimed at white-collar workers.

The company is hiring across New York, San Francisco, Boston, Chicago, Austin, and Toronto as it works to convert its funding into deeper product capability — and a bigger bet that the most durable AI businesses will be built inside the industries that have been hardest, not easiest, to automate.