Booking a doctor’s appointment seems simple, but anyone who has ever tried calling a busy medical office knows how quickly it can turn into a nightmare. You call, get sent to voicemail, leave a message, wait for a callback that never comes, try again the next day, and repeat the cycle until you give up or your health issue gets worse. It is frustrating for the patient and, oddly enough, it is also a massive problem for the offices themselves, which lose bookings, waste staff time, and deal with patients referred to the wrong place, who forget to fill out paperwork, or simply no-show on the scheduled date.
This is exactly the problem two 29-year-olds decided to tackle head-on, and the result surprised even the most skeptical investors in the health tech space.
Jon Wang and Jeff Liu, co-founders and co-CEOs of Assort Health, built an AI voice agent capable of handling the entire medical appointment scheduling process autonomously — no endless hold times and no annoying hold music. Their solution is not just a glorified chatbot that answers basic questions. It is a full-blown system that can understand the patient’s context, scan through doctors’ calendars, match available time slots with the type of appointment needed, and finalize the booking without any human intervention at any step along the way. For anyone working in digital health, this represents a pretty significant shift in how clinics and hospitals interact with their patients on a daily basis.
And there is a fun detail worth mentioning: the duo became known for wearing cowboy hats everywhere, including board meetings and fundraising rounds. I just liked the look, the vibe. It is the wild west of healthcare, Liu jokes. It might seem like a small thing, but it has become part of the company’s cultural identity. JP Sanday, a partner at Menlo Ventures, puts it well: it is a good rallying cry for the team and a great way to build connection among people.
And the market responded fast 💥
In just 14 months, the San Francisco-based startup closed three funding rounds, reaching a stunning valuation of $1.2 billion, with the most recent raise of $120 million led by Menlo Ventures. That figure represents a jump of more than 70% over the $700 million valuation recorded the previous September. In total, Assort Health has raised $222 million from heavyweight investors including Lightspeed, First Round, and Chemistry. For anyone following the startup ecosystem, reaching unicorn status in just over a year is something most companies take five to ten years to achieve — when they achieve it at all.
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From 45 closed doors to $1.2 billion
Before earning the unicorn title, the two founders knocked on the doors of 45 different investors, getting rejected by most of them, including the very VC who eventually introduced them to other partners. Most people passed on us because they didn’t believe in us, Liu recalls. It was not until March 2024 that they managed to close a $3.5 million seed round led by Quiet Capital. This part of the story tends to get left out when people talk about successful startups, but it matters a lot. Because it shows that the road to startup funding is rarely linear, especially when the proposed product is ambitious and the market is still learning to trust artificial intelligence-based solutions in sensitive areas like healthcare.
The company started operations in January 2023, after the two founders were connected by an investor and instantly clicked. Their backgrounds are worth knowing. Liu grew up in Northern Virginia, wanted to be a fighter pilot, and once volunteered at a hospital doing patient transport. He started college at Duke on a pre-med track but switched to computer science. After that, he worked in AI and healthcare operations, including at Athelas, valued at $7 billion, where he led product engineering and helped build one of the first systems that listens to conversations between doctors and patients and turns everything into clinical notes.
Wang grew up in Minnesota, the son of an immigrant physician who dreamed of seeing him follow the same career path. He got into medical school at UCSF but left to start a company after co-authoring seven papers on AI and healthcare. He co-founded Shimmer, a Y Combinator-backed startup focused on preventive mental health, and spent a year as chief of staff at Elemy, a startup focused on autism care. When the two teamed up, the combination of clinical vision and technical chops made complete sense for the kind of problem they set out to solve.
Wang and Liu did not give up after the rejections, and they did not radically change the product to please investors who did not believe in the idea. They kept refining the technology, pursuing their first real customers, and collecting data that could prove the AI agent actually worked in a clinical environment. When the numbers started showing up, the investors who had previously shut the door began watching the company closely, observing the growth unfold.
What the Assort Health AI agent actually does
Appointment scheduling might seem like a simple problem at first glance, but when you start breaking down the process inside a clinic with hundreds of patients a week, the complexity shows up fast. As Sanday from Menlo explains, scheduling is dictated by all those complex rules that exist in a printed binder at each office or that live inside people’s heads. The agent needs to understand why the patient is calling, identify which specialty or specific doctor is needed, verify real-time availability, and confirm details. Everything that used to require a trained receptionist available during business hours now happens automatically, at any time of day or night.
Beyond talking to patients, the system also records text transcripts of each call for later analysis, which opens the door for continuous improvements. The technology is already in use at offices of roughly 15,000 doctors across the United States, mainly in specialties like orthopedics and dermatology — a pretty impressive scale for such a young startup 🚀
The operational results are striking. The company says it has achieved a 75% reduction in patient hold times on the phone, and only 5% of callers hang up before being handled by the voice agent. Forbes estimates that Assort’s annualized revenue already exceeds $30 million, and the company itself says that number has grown twenty-fold over the past 15 months — a pace that, according to Wang, is faster than buzzy startups like Harvey in legal tech and Decagon in customer support.
From scheduling to way beyond it
Scheduling was just the entry point. From there, Assort Health started expanding into other patient interactions, including callback management, rescheduling, document organization, and even billing. The company is building technology capable of remembering patients across all these different tasks so they do not have to keep repeating their medical history or service requests over and over. Liu says $70 million of the new funding will go specifically toward developing that technology, with a launch expected in the third quarter.
190 million interactions and what that number reveals
The health tech platform built by Assort Health has already processed more than 190 million patient interactions, and that number needs some context to fully make sense. Each interaction represents a moment when a patient tried to schedule, cancel, reschedule, or get information about an appointment — and the AI agent was able to handle that request without a human attendant stepping in. Multiply that by the amount of time a receptionist would spend on each of those calls, and the operational impact for partner practices is enormous.
That volume also carries another very important value: it represents a massive dataset of real-world information, generated in clinical settings, that feeds the system’s continuous learning. Unlike models trained only on synthetic data or generic datasets, Assort Health’s agent learns from real interactions, with real patients, in real appointment scheduling contexts. This creates a competitive advantage that gets harder to replicate as the data pool grows.
The company started by focusing on orthopedics, a complex specialty because the doctors are highly specialized — a sports medicine physician is not the same as a hand surgeon, and each one has strict rules about who they will or will not see. From there, it expanded into 22 other specialties, including dermatology and urology, and recently signed its first health system, John Muir Health, which has more than a thousand doctors and operates two major medical centers in California.
The real proof came from the offices themselves
Dr. Parinita Amin, CEO of MDCS Dermatology, with locations in New York and New Jersey, was one of the earliest customers, about two years ago. She was looking for help managing the clinic’s schedule, which involves 33 providers and 120,000 appointments a year. After interviewing several vendors and realizing that many did not deliver what they promised in their demos, she was so cautious that she actually asked Wang if he needed more time to mature the technology before committing. She opted for a phased rollout instead.
The results exceeded expectations. According to Amin, bookings grew by more than 20%, partly because the clinic started capturing patients who previously gave up when they could not reach anyone on weekends. Whenever you get into that phone tag game, things slip through the cracks, she says. And she adds something that speaks volumes: if you ask anyone on the team whether they want to go back to the old way, the answer is a resounding absolutely not.
An increasingly hot market
Over the past three years, AI-powered medical scheduling has become a competitive field, with companies like EliseAI, backed by Andreessen Horowitz and valued at $2.2 billion, also eyeing the sector’s potential. For Wang, that is actually welcome. There is always a wave of new entrants that show up and signal that this is a real market, he says, before throwing in a lighthearted jab: the hope is that, at the end of the day, the big loser will be the good old landline phone.
Assort Health is one of the most concrete examples of how a well-applied AI agent can transform processes that seem simple but hide enormous operational complexity. The company’s journey, with all its rejections and lessons learned along the way, shows that the startup funding market is increasingly willing to bet big when the product has real traction and the team demonstrates consistent execution capability.
