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Exclusive: Assort Health raises $76 million Series B to build on voice AI healthcare platform

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Like so many people with busy 9-to-5s, high school teacher Suzanne Grinberg has a scheduling problem: By the time she has a free moment in her day to call her doctor to make an appointment, the doctor’s office is already closed. 

So, when she recently called her dermatologist before business hours, Grinberg expected to leave a voicemail—but instead got a pleasant surprise. “At 5:30 AM, when I was putting on my makeup to go to work, I was able to make my appointment,” she said.

Grinberg’s dermatologist had started using a voice AI system called Assort Health, a startup building specialty-specific agents for healthcare. The company was founded in 2023 by Jeff Liu and Jon Wang, who together spent two years getting to know the healthcare system before the startup picked up steam. 

“What’s really interesting about our space is that voice AI and LLMs have actually been around for a while,” said Liu, who is the co-CEO. “But healthcare is so complicated. They have binders, spreadsheets full of these really complicated rules, and that’s prevented automation from helping providers—despite them really needing help.” 

Assort, which to date has collected approximately 42 million patient interactions on its platform, raised its $22 million Series A in April, with Term Sheet breaking the news. They’re now back, just a few months later: Assort has raised a $76 million Series B, led by Lightspeed, Fortune can exclusively report. First Round and Chemistry, which led the Series A, returned as investors for this round and were joined by Felicis, A*, Liquid 2 Ventures, and Quiet. This brings Assort’s total capital raised to date to $102 million, and to one doctor, the tech solves a key business problem. 

“The problem in any business, if you don’t have individuals working at the top of their license, is that you’re leaving money on the table,” said Dr. Titus Abraham, physician at Annapolis Internal Medicine, a practice using Assort. “They’re doing things that can be done better by someone else or by a different system…I shouldn’t be signing paperwork or taking calls all day.”

The end game, says cofounder and co-CEO Wang, is “moving from a reactive system where you as a patient have to schedule a primary care appointment six months out, to a system that’s more proactive and preventative.” For example, Wang says, “if you know after you get your cortisone injection in your right knee, you need to schedule another appointment three months out, we’re going to have an agent that’s going to be there for you, helping make sure you get your time booked right.”

It’s a lofty goal, to be sure, and not one any single company can accomplish in a system as labyrinthine and layered as U.S. healthcare. All the same, this is a moment characterized by a unique level of optimism (and venture dollars) flowing into a wave of young startups at the intersection of healthcare and AI. Lightspeed partner Galym Imanbayev attributes this momentum to “the surface area by which technology and AI can impact healthcare [having] dramatically expanded…leading to unprecedented ROI demonstrated tangibly by customers.” Olympic gold medal speedskater and Assort investor Apolo Ohno puts it more directly: “The radical speed at which AI is transforming industries right now is not debatable.”

For Assort’s Liu, the ultimate value is in the patient experience: “It’s a painful process to get access to care. And when we solve this critical problem in a way patients and providers haven’t seen before, it’s this magical moment.”

See you tomorrow,

Allie Garfinkle
X:
@agarfinks
Email: alexandra.garfinkle@fortune.com
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Venture Deals

Alvys, a Solana Beach, Calif.-based developer of AI technology for freight operations, raised $40 million in Series B funding. RTP Global led the round and was joined by Alpha Square Group and others.

OXCCU, an Oxford, U.K.-based sustainable aviation fuel company, raised $28 million in Series B funding from International Airlines Group, Safran Corporate Ventures, Orlen, Aramco Ventures, and others.

Paid, a London, U.K.-based monetization and cost tracking platform for AI agents, raised $21.6 million in seed funding. Lightspeed Venture Partners led the round and was joined by FUSE and existing investor EQT Ventures.

Lexroom.ai, a Milan, Italy-based developer of legal AI software, raised $19 million in Series A funding. Base10 Partners led the round.

Mondoo, a San Francisco-based developer of a vulnerability management platform for agentic AI, raised $17.5 million in funding. HV Capital led the round and was joined by T.Capital and existing investors Atomico, Firstminute Capital, and System.One.

Goodfit, a London, U.K.-based data platform for go-to-market strategy, raised $13 million in funding. Notion Capital led the round and was joined by Salica Investments, Inovia Capital, Robin Capital, Common Magic, and Andrena Ventures.

Neura Health, a NYC-based virtual neurology clinic, raised $11.4 million in Series A funding. The American Heart Association’s Go Red for Women Venture Fund led the round and was joined by Norwest Venture Partners, Koch Disruptive Technologies, Esplanade Ventures, and others.

Confido Health, a New York City-based agentic AI platform for health care operations, raised $10 million in Series A funding. Blume Ventures led the round and was joined by Schema Ventures, Vicus Ventures, and others.

InOrbit.AI, a Mountain View, Calif.-based AI-powered robot orchestration platform, raised $10 million. L’ATTITUDE Ventures and Globant Ventures led the round.

Supernova, a Dover, Del.-based developer of an AI-powered collaborative workspace for product teams, raised $9.2 million in Series A funding. Taiwania Capital led the round and was joined by J&T Ventures, Reflex Capital, and existing investors.

Arqh, a Zurich, Switzerland-based AI company developing a decision-intelligence engine for complex operations, raised $3.8 million in pre-seed funding. Founderful led the round and was joined by Merantix Capital.

Private Equity

AAi Labels & Decals, backed by Portrait Capital, acquired Sticker Ranch, a San Antonio, Texas-based labels and stickers provider. Financial terms were not disclosed.

Northrim Horizon acquired ACG Systems, an Annapolis, M.D.-based systems integrator and technical service provider for wireless communication systems. Financial terms were not disclosed.

Towne Park, backed by Greenbriar Equity Group, acquired Frogparking, a Palmerston, New Zealand-based parking systems company. Financial terms were not disclosed. 

Funds + Funds of Funds

Concept Ventures, a London, U.K.-based venture capital firm, raised $88 million for its second fund focused on pre-seed companies.

People

GV, a San Francisco-based venture capital firm, promoted Vidu Shanmugarajah to general partner.

Turnspire Capital Partners, a New York City-based private equity firm, promoted Ahdiv Nathan to principal.

Introducing the Fortune AIQ 50 ranking

Today, we published the Fortune AIQ 50, a new ranking that evaluates how Fortune 500 companies are actually deploying AI, and how technology leaders value those investments relative to industry peers. The ranking is a record of how 18 sectors across the Fortune 500, including financials, health care, and retailing, are utilizing AI to personalize customer experiences, provide groundbreaking data analysis, optimize supply chains, and more. Explore the list, and catch up on our ongoing Fortune AIQ series.



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Mark Zuckerberg renamed Facebook for the metaverse. 4 years and $70B in losses later, he’s moving on

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In 2021, Mark Zuckerberg recast Facebook as Meta and declared the metaverse — a digital realm where people would work, socialize, and spend much of their lives — the company’s next great frontier. He framed it as the “successor to the mobile internet” and said Meta would be “metaverse-first.”

The hype wasn’t all him. Grayscale, the investment firm specializing in crypto, called the Metaverse a “trillion-dollar revenue opportunity.” Barbados even opened up an embassy in Decentraland, one of the worlds in the metaverse. 

Five years later, that bet has become one of the most expensive misadventures in tech. Meta’s Reality Labs division has racked up more than $70 billion in losses since 2021, according to Bloomberg, burning through cash on blocky virtual environments, glitchy avatars, expensive headsets, and a user base of approximately 38 people as of 2022.

For many people, the problem is that the value proposition is unclear; the metaverse simply doesn’t yet deliver a must-have reason to ditch their phone or laptop. Despite years of investment, VR remains burdened by serious structural limitations, and for most users there’s simply not enough compelling content beyond niche gaming.

A 30% budget cut 

Zuckerberg is now preparing to slash Reality Labs’ budget by as much as 30%, Bloomberg said. The cuts—which could translate to $4 billion to $6 billion in reduced spend—would hit everything from the Horizon Worlds virtual platform to the Quest hardware unit. Layoffs could come as early as January, though final decisions haven’t been made, according to Bloomberg. 

The move follows a strategy meeting last month at Zuckerberg’s Hawaii compound, where he reviewed Meta’s 2026 budget and asked executives to find 10% cuts across the board, the report said. Reality Labs was told to go deeper. Competition in the broader VR market simply never took off the way Meta expected, one person said. The result: a division long viewed as a money sink is finally being reined in.

Wall Street cheered. Meta’s stock jumped more than 4% Thursday on the news, adding roughly $69 billion in market value.

“Smart move, just late,” Craig Huber of Huber Research told Reuters. Investors have been complaining for years that the metaverse effort was an expensive distraction, one that drained resources without producing meaningful revenue.

Metaverse out, AI in

Meta didn’t immediately respond to Fortune’s request for comment, but it insists it isn’t killing the metaverse outright. A spokesperson told the South China Morning Post that the company is “shifting some investment from Metaverse toward AI glasses and wearables,” point­ing to momentum behind its Ray-Ban smart glasses, which Zuckerberg says have tripled in sales over the past year.

But there’s no avoiding the reality: AI is the new obsession, and the new money pit.

Meta expects to spend around $72 billion on AI this year, nearly matching everything it has lost on the metaverse since 2021. That includes massive outlays for data centers, model development, and new hardware. Investors are much more excited about AI burn than metaverse burn, but even they want clarity on how much Meta will ultimately be spending — and for how long.

Across tech, companies are evaluating anything that isn’t directly tied to AI. Apple is revamping its leadership structure, partially around AI concerns. Microsoft is rethinking the “economics of AI.” Amazon, Google, and Microsoft are pouring billions into cloud infrastructure to keep up with demand. Signs point to money-losing initiatives without a clear AI angle being on the chopping block, with Meta as a dramatic example.

On the company’s most recent earnings call, executives didn’t use the word “metaverse” once.



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Robert F. Kennedy Jr. turns to AI to make America healthy again

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HHS billed the plan as a “first step” focused largely on making its work more efficient and coordinating AI adoption across divisions. But the 20-page document also teased some grander plans to promote AI innovation, including in the analysis of patient health data and in drug development.

“For too long, our Department has been bogged down by bureaucracy and busy-work,” Deputy HHS Secretary Jim O’Neill wrote in an introduction to the strategy. “It is time to tear down these barriers to progress and unite in our use of technology to Make America Healthy Again.”

The new strategy signals how leaders across the Trump administration have embraced AI innovation, encouraging employees across the federal workforce to use chatbots and AI assistants for their daily tasks. As generative AI technology made significant leaps under President Joe Biden’s administration, he issued an executive order to establish guardrails for their use. But when President Donald Trump came into office, he repealed that order and his administration has sought to remove barriers to the use of AI across the federal government.

Experts said the administration’s willingness to modernize government operations presents both opportunities and risks. Some said that AI innovation within HHS demanded rigorous standards because it was dealing with sensitive data and questioned whether those would be met under the leadership of Health Secretary Robert F. Kennedy Jr. Some in Kennedy’s own “Make America Health Again” movement have also voiced concerns about tech companies having access to people’s personal information.

Strategy encourages AI use across the department

HHS’s new plan calls for embracing a “try-first” culture to help staff become more productive and capable through the use of AI. Earlier this year, HHS made the popular AI model ChatGPT available to every employee in the department.

The document identifies five key pillars for its AI strategy moving forward, including creating a governance structure that manages risk, designing a suite of AI resources for use across the department, empowering employees to use AI tools, funding programs to set standards for the use of AI in research and development and incorporating AI in public health and patient care.

It says HHS divisions are already working on promoting the use of AI “to deliver personalized, context-aware health guidance to patients by securely accessing and interpreting their medical records in real time.” Some in Kennedy’s Make America Healthy Again movement have expressed concerns about the use of AI tools to analyze health data and say they aren’t comfortable with the U.S. health department working with big tech companies to access people’s personal information.

HHS previously faced criticism for pushing legal boundaries in its sharing of sensitive data when it handed over Medicaid recipients’ personal health data to Immigration and Customs Enforcement officials.

Experts question how the department will ensure sensitive medical data is protected

Oren Etzioni, an artificial intelligence expert who founded a nonprofit to fight political deepfakes, said HHS’s enthusiasm for using AI in health care was worth celebrating but warned that speed shouldn’t come at the expense of safety.

“The HHS strategy lays out ambitious goals — centralized data infrastructure, rapid deployment of AI tools, and an AI-enabled workforce — but ambition brings risk when dealing with the most sensitive data Americans have: their health information,” he said.

Etzioni said the strategy’s call for “gold standard science,” risk assessments and transparency in AI development appear to be positive signs. But he said he doubted whether HHS could meet those standards under the leadership of Kennedy, who he said has often flouted rigor and scientific principles.

Darrell West, senior fellow in the Brooking Institution’s Center for Technology Innovation, noted the document promises to strengthen risk management but doesn’t include detailed information about how that will be done.

“There are a lot of unanswered questions about how sensitive medical information will be handled and the way data will be shared,” he said. “There are clear safeguards in place for individual records, but not as many protections for aggregated information being analyzed by AI tools. I would like to understand how officials plan to balance the use of medical information to improve operations with privacy protections that safeguard people’s personal information.”

Still, West, said, if done carefully, “this could become a transformative example of a modernized agency that performs at a much higher level than before.”

The strategy says HHS had 271 active or planned AI implementations in the 2024 financial year, a number it projects will increase by 70% in 2025.



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Construction workers are earning up to 30% more in the data center boom

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Big Tech’s AI arms race is fueling a massive investment surge in data centers with construction worker labor valued at a premium. 

Despite some concerns of an AI bubble, data center hyperscalers like Google, Amazon, and Meta continue to invest heavily into AI infrastructure. In effect, construction workers’ salaries are being inflated to satisfy a seemingly insatiable AI demand, experts tell Fortune.

In 2026 alone, upwards of $100 billion could be invested by tech companies into the data center buildout in the U.S., Raul Martynek, the CEO of DataBank, a company that contracts with tech giants to construct data centers, told Fortune.

In November, Bank of Americaestimated global hyperscale spending is rising 67% in 2025 and another 31% in 2026, totaling a massive $611 billion investment for the AI buildout in just two years.

Given the high demand, construction workers are experiencing a pay bump for data center projects.

Construction projects generally operate on tight margins, with clients being very cost-conscious, Fraser Patterson, CEO of Skillit, an AI-powered hiring platform for construction workers, told Fortune.

But some of the top 50 contractors by size in the country have seen their revenue double in a 12-month period based on data center construction, which is allowing them to pay their workers more, according to Patterson.

“Because of the huge demand and the nature of this construction work, which is fueling the arms race of AI… the budgets are not as tight,” he said. “I would say they’re a little more frothy.”

On Skillit, the average salary for construction projects that aren’t building data centers is $62,000, or $29.80 an hour, Patterson said. The workers that use the platform comprise 40 different trades and have a wide range of experience from heavy equipment operators to electricians, with eight years as the average years of experience.

But when it comes to data centers, the same workers make an average salary of $81,800 or $39.33 per hour, Patterson said, increasing salaries by just under 32% on average.

Some construction workers are even hitting the six-figure mark after their salaries rose for data center projects, according to The Wall Street Journal. And the data center boom doesn’t show any signs it’s slowing down anytime soon.

Tech companies like Google, Amazon, and Microsoft operate 522 data centers and are developing 411 more, according to The Wall Street Journal, citing data from Synergy Research Group. 

Patterson said construction workers are being paid more to work on building data centers in part due to condensed project timelines, which require complex coordination or machinery and skilled labor.

Projects that would usually take a couple of years to finish are being completed—in some instances—as quickly as six months, he said.

It is unclear how long the data center boom might last, but Patterson said it has in part convinced a growing number of Gen Z workers and recent college grads to choose construction trades as their career path.

“AI is creating a lot of job anxiety around knowledge workers,” Patterson said. “Construction work is, by definition, very hard to automate.”

“I think you’re starting to see a change in the labor market,” he added.



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