Signal and Noise in Healthtech
Arvita TripatiHelps investors separate real enterprise value from hype. Examines the hidden product, regulatory, workflow, data, and commercial risks that determine whether a healthcare or healthtech company is truly buyable, scalable, and defensible.
| Platform |  | Pricing | Only free issues | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 7 | Founded | a year ago | Last Issue | 2 months ago |
| Active | |||||
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signalandnoiseinhealthtech.substack...Latest Issues
OpenEvidence's moat just got a stress test
OpenEvidence raised at a 3.5 billion dollar valuation as the fastest-growing physician app on record. Last week a Nature Medicine study found that on the medical knowledge task it is built for, it does not beat the free frontier models any...
How to tell a wearable moat from a head start
This is the companion to “Everyone is buying the same sensor.” That piece was for the founders building these companies. This one is for the people deciding whether to wire the check.
The setup is the same. The consumer health stack is com...
When Experimental Revenue Meets Regulatory Cost
The retention metrics in the data room looked clean. The quality system behind them was built for a customer base that might not exist in eighteen months.
A venture operating partner I met with recently predicted what she called “the gross...
AI Story vs AI Economics
Across more than a dozen healthtech, medtech, diagnostics, and life sciences company reviews this year, one AI value creation story keeps showing up: gross margin expansion, shorter implementation cycles, and enterprise account expansion th...
104% NRR is not product-market fit
The market loves clean SaaS metrics.
Healthtech AI makes some of them dangerous.
A 104% net revenue retention number at a physician-facing AI company looks like product-market fit. It may be. Or it may be two enterprise accounts expanding...
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