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NexHealth’s infrastructure serves 89 million patients and, per Al, 81% of new AI…

2026-08-03 · 15:19 UTC ·@ThePeelPod ·2 min read

Brief

NexHealth scaled to 89 million patients and claims 81% of new AI healthcare startups run on its platform, yet deliberately delayed user‑facing AI despite building two features in three months after ChatGPT because healthcare demands accuracy and compliance. The company survived a cash crisis ($4k in bank, maxed AmEx), raised early customer/professor funding ($391k), was saved by a $36k pre‑pay, and now positions AI value in chips, models, and the action layer.

Why it matters

NexHealth’s infrastructure serves 89 million patients and, per Al, 81% of new AI healthcare startups are built on it.

Key details

  • After ChatGPT, NexHealth built two AI features within three months but released no user‑facing AI, citing the need for accuracy, compliance, and reliability in healthcare; the company intentionally stayed patient for roughly three years and expects AI value to accrue to chips, models, and the action layer.
  • NexHealth nearly ran out of cash ($4,000 in the bank and a maxed‑out AmEx), raised $391,000 from professors and customers, was rescued by a $36,000 pre‑pay, later raised $176M they 'didn't need,' and spent half their Series A on an acquisition.
Source evidence

Why @alfromnexhealth didn't go all-in on AI right after ChatGPT launched:

"We built two AI features into our product within three months. But we never released anything user facing.

Healthcare is one of those areas where you have to be accurate, compliant, and it has to work."

Video

Turner Novak 🍌🧢 (@TurnerNovak)

New @ThePeelPod with @alfromnexhealth

Today @nexhealthHQ infrastructure serves 89 million patients and 81% of new AI healthcare startups are built on it.

But at one point, the company had $4k in the bank, a maxed-out Amex card, and was on the brink of running out of cash.

I sat down with Al to talk about why 75% of dentists still run a server in their closet, the reason innovation is so hard in healthcare, and why AI value will accrue to chips, models, and the action layer.

Full episode here + links below.

Timestamps:
0:00 Healthcare skipped 3 platform shifts and went straight to AI
4:10 75% of dentists still have on-prem servers
10:05 How data interoperability holds back healthcare innovation
16:02 Why everyone blames Epic
20:15 Building the developer platform for healthcare
24:36 Why everyone fails to fix the problem
29:11 Fragmented markets enabled developer platforms
32:32 Working as a receptionist at a doctor’s office
36:13 Building a prototype on Twilio
39:15 How incumbents went from blocking to partnering
46:05 Canvassing Soho dentists door-to-door
53:47 Reverse-engineering 40-year old databases
56:21 Funding NexHealth with side hustles for two years
57:30 The scheduling wedge no one could match
1:02:20 Raising $391k from professors and customers
1:03:46 Running out of cash, why customers kept churning
1:07:45 $4,000 in the bank and a maxed-out Amex
1:11:12 The $36k pre-pay that saved the company
1:13:24 NexHealth’s three businesses today
1:20:18 Payments and the “admin-day” problem
1:26:15 72% sales win rate
1:28:27 The term sheet signed the week before COVID
1:30:26 Spending half the Series A on an acquisition
1:33:47 Raising $176M they didn't need
1:37:28 Why starting before 2022 is an advantage
1:42:22 Where AI value accrues: chips, models, the action layer
1:44:55 81% of AI products are built on NexHealth
1:48:24 Staying patient for three years after ChatGPT
1:51:25 Competitors building on their API
1:54:02 “We’re a tech company, not healthcare company”
1:56:09 Hiring from outside healthcare
1:58:34 Shoes, email over Slack
2:01:21 What AI changed inside the company
2:04:16 Inspiration from Microsoft in 1977 - 1990

Video

— https://nitter.net/TurnerNovak/status/2082854053516615920#m