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Al from NexHealth says AI value will accrue in three waves

2026-08-06 · 20:03 UTC ·@ThePeelPod ·3 min read

Brief

The podcast with Al from NexHealth argues that most future AI economic value will sit in an "action layer" that sits between LLMs and the physical world, following earlier value accrual to Nvidia‑class chip makers and R&D/model builders such as OpenAI and Anthropic. Al illustrates the action layer with a healthcare example: an LLM chatbot must query real‑time schedules (“what day is the doctor in?”) and write bookings back to avoid no‑shows. NexHealth positions itself as that infrastructural glue—serving 89 million patients and claiming that 81% of new AI healthcare startups build on its platform—while highlighting why healthcare lags (75% of dentists run on‑prem servers, poor interoperability) and how fragmentation enabled developer platforms. He also recounts near‑death cash moments ($4k in the bank, maxed AmEx), early raises ($391k from professors/customers), a $36k pre‑pay lifeline, and later large financing (a term sheet before COVID and $176M raised).

Why it matters

Al from NexHealth says AI value will accrue in three waves: (1) chip makers like Nvidia, (2) R&D/model builders such as OpenAI and Anthropic, and (3) the emerging action layer that connects LLMs to real‑world, real‑time actions (e.g., checking a doctor’s schedule and writing a booking back to their calendar).

Key details

  • NexHealth claims major platform scale: its infrastructure serves 89 million patients and, per the episode, 81% of new AI healthcare startups (and 81% of AI products) are built on NexHealth’s platform.
  • Healthcare remains highly legacy: 75% of dentists still run on‑prem servers, data interoperability constrains innovation, and fragmented markets created the opportunity for developer platforms like NexHealth.
  • NexHealth’s founding story involved acute cash strain—$4,000 in the bank and a maxed‑out AmEx—followed by fundraising milestones including $391,000 from professors/customers and a $36,000 pre‑pay that 'saved the company'; later rounds included a term sheet the week before COVID and raising $176M the company says it 'didn't need.'
Source evidence

I asked @alfromnexhealth why most future value in AI will accrue to the action layer:

"First, it was the chip makers, like Nvidia.

Second, it’s OpenAI and Anthropic. The companies that do the R&D. The research to build the actual LLMs.

The third wave, which hasn’t truly come yet, but more and more of the ecosystem is realizing it, is the companies and the infrastructure that takes the LLMs and enables them to actually action stuff in the real world.

This is the layer that sits between the physical world and the software world. Where these LLMs can then actually go into the physical world and action that data.

A very basic example: if you’re a healthcare practice today, you can use the OpenAI API to build a chatbot product on your website.

A patient can chat with it about their condition. And it’ll recommend the right provider, and a time slot in the office to book an appointment.

That chatbot or LLM needs to connect to the physical world. "What day is the doctor in the office? What room in the office is available?". All in real time. Because the patient is talking to that chatbot in real time.

To then surface, “Hey, here’s what’s available,” and take your information and write it back as well. Otherwise the patient will show up and it won’t be on their calendar.

So if you just track the hype cycle: it's chip makers, the companies that build the LLMs, and then the action layer that sits between the LLMs and the physical world."

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