The problem
Health systems are stuck in AI pilots with no safe, governed way to roll AI out across clinical and admin work
What they do
Enterprise generative-AI platform and governance layer that helps health systems deploy AI safely
Traction 500,000+ users at health systems representing ~7% of US hospital revenue; UTMB $15M run-rate impact
Hiring trend
- Open roles
- 20
- Ops roles
- 3
- Headcount
- ~175
Headcount ~175, +337% YoY (LinkedIn est.); 24 open roles, many forward-deployed
Hiring in
- Palo Alto
- Remote (US)
Funding
- Last round
- $125M
- Stage
- Series B
- Date
- Mar 2026
Led by NEA
- Hiring+1.520 open roles on the live job board (10–29 roles = +1.5)
- Funding recency+1.5Series B · $125M, Mar 2026 (7 months ago): 6–12 months = +1, $100M+ round +0.5
- Traction+1.5Strong growth: 500,000+ users at health systems representing ~7% of US hospital revenue; UTMB $15M run-rate impact
- Red flags0None found in the last 24 months
- Total4.51.5 + 1.5 + 1.5 − 0 = 4.5 → Race (4.25–4.74)
Distance (10K) is a separate read on how long the lead can last. It doesn't change the score.
Distance
10K · edge: hard to leave
Real early adoption (UT System, Emory, LCMC, ~7% of US hospital revenue) but it sits on top of Epic, whose own AI tools and Microsoft's reach the same CIO buyer directly; heavy platform exposure.
Sources: Cathay Capital: 500,000 users, ~7% of US hospital revenue (Mar 2026) ↗ · Simplify: risks incl. incumbents undercutting healthcare AI infrastructure ↗
Last checked Oct 25, 2026