.health Confidential

Executive one-pager · Seed round

The ambient-AI-native EMR + RCM for independent practices

REV.health gives time back to the exam room — the note is done before the clinician leaves the room — and gets independent practices paid correctly the first time. One platform: EHR + practice management + revenue-cycle, AI-native from day one.

Raising a $4M seed at 20% ownership ($20M post-money) to reach certified general availability · founders@rev.health

The moat: REV is a self-learning system — it learns from every encounter and every corrected mistake, so accuracy and capture compound over time. No incumbent does this: they’re digital paper-and-pencil — static, rules/template-based, with an ambient scribe bolted on at best.

25.4x
Gross MOIC at the 10× base case · 15.3× at the 6× downside floor
$50.9M
Exit ARR run-rate
$101.8M
Investor proceeds at the 10× base case (→ $61M at the 6× floor)
78%
Blended gross margin at scale (modeled target)

The problem

Independent 1–5 clinician practices — the largest underserved segment in ambulatory health IT — lose 2–3 hrs/night to “pajama-time” charting, leak 5–10% of revenue to fragmented billing and untriaged denials, and run 30–60 day AR cycles. Incumbents have outgrown this buyer.

Why now

A once-per-decade regulatory window (USCDI v3, HTI-1, TEFCA, CMS-0057-F prior-auth APIs) forces every incumbent to retrofit. We start native — FHIR-native, AI-native and TEFCA-connected from day one.

The product

One data model across 10 modules — ambient clinical doc, scheduling, eligibility & prior-auth, eRx/EPCS, and integrated RCM & denials in the seed-funded wedge. The note is coded and traceable to the audio; charge capture → 10K+ rule scrubbing → auto-posting → AI denial triage targets ≥98% first-pass clean claims.

How we're different

  • Structure-first ambient scribe (writes coded fields, not a transcript)
  • Turn-key integrated RCM — no billing coordinator required
  • Resource-graph scheduling — ~20% utilization lift in our data
  • ML-based, not rules-based — ≥15% more efficient as it learns

Business model

$595/provider/mo SaaS + 4.9% of collections (90% attach) — all-inclusive, no AI upcharge. ~$59K revenue/provider/yr, ~$147K ACV/practice. Room to raise rate & collection % as the platform hardens and new specialties come on.

Market

$16.4B TAM (~280K US primary-care physicians × $4,898/mo blended) · the independent PCP groups we serve (~136K practices) are the SAM · ~0.3% SOM (866 providers of ~280K PCPs; $50.9M ARR) · expansion into high-collections specialties (ortho, cardio, GI) is a pure ACV lever after the primary-care beachhead.

The plan

2028 GA after ONC certification; self-funded to exit on the seed — no Series A or B required. Path to 346 practices / 866 providers and a $50.9M exit ARR run-rate by 2032, EBITDA-positive ~month 39, ~$33.1M run-rate EBITDA at 78% gross margin (modeled at-scale target). These are at-scale figures the model earns as it learns: Year 1 runs below ~$750K collections per provider and ramps toward the ~$1.07M/provider at-scale level as the system improves — capture and margin build over time, not switched on day one. Key dependency: growth runs ~85% through the captive partner channel placing acquired networks onto REV, with a lean ~15% external sales motion sourcing those network deals; if that channel underdelivers, growth slows — the lean, demand-triggered cost base is what lets us self-fund through a slower channel.

The return

$4M → $101.8M at a 10× revenue exit (base case) — 25.4x gross MOIC, ~$97.8M gain, on 20% seed ownership held to exit with no Series A or B dilution. Downside floor: a 6× exit → $61.1M / 15.3x. 6× sits right at the ~6.1× RCM-deal average, and 10× is consistent with health-IT take-privates — athenahealth sold for $17B in 2021 (~11–12× revenue) and $5.7B in 2019. Live, formula-driven model in the portal.

Full deck (PDF) Investor portal Live demo ↗

On margins: athenahealth — the category benchmark — runs ~54% gross margin and mid-teens operating margin as a broad multi-specialty platform carrying a large human RCM services workforce. REV's higher modeled at-scale margins reflect a PCP-first, ambient-AI-native model that automates coding + denials, taking RCM cost-to-serve toward ~1.3% of collections at scale (~15% better RCM efficiency than the incumbent). Margins shown are modeled at-scale targets. The ~78% gross margin is the primary-care beachhead; other specialties and non-ambulatory settings will almost certainly be lower.

Team: Patrick Feeney (Co-founder & CEO) · Jeff Hughes (Co-founder & CTO) · Daniel Dow, M.D. (Co-founder & SME). Confidential.