OpenEvidence
Worth-Joining Index · Scorecard
v2.1 ALPHA · 2026-08Career Score
65/100
Coverage
71%
Verified
0%
Stage cohort
Growth
Vibe Check
🎪 community voting coming soon
Latest valuation
$12B (Series D, 2026-01)
Total raised
~$700M raised in trailing 12 months as of 2026-01 (life-to-date total not separately disclosed)
Traction · Key numbers
Funding
Total raised
~$700M raised in trailing 12 months as of 2026-01 (life-to-date total not separately disclosed)
Rounds
4
Valuation pace
Valuation rose from $1B
$250M
Series D · 2026-01 · valuation $12B post (Series D, 2026-01) · led by Thrive Capital, DST Global
Valuation doubled in ~3 months; total raised nears $700M
$200M
Series B extension · 2025-10 · valuation $6.1B post · led by GV
With: Sequoia, Kleiner Perkins, Blackstone, Thrive, Coatue, BOND, Craft · Came just 3 months after prior round
$210M
Series B · 2025-07 · valuation $3.5B post · led by Google Ventures, Kleiner Perkins
$75M
Series A · 2025-02 · valuation $1B post
Reached unicorn status
▸Investor lineup escalated fast: from ordinary Series A backers to Google Ventures/Kleiner Perkins at B, then Thrive Capital/DST Global at D — top-tier funds piling in within a year implies a growth curve steep enough to justify the valuation jumps
▸The financing cadence is itself a risk signal: 4 rounds in 11 months with valuation up 12x from $1B to $12B looks more like a scarcity premium than steady-state compounding
▸GV/Kleiner Perkins entering at Series B — funds known for later-stage diligence — suggests physician retention and usage depth likely passed real scrutiny, not just top-line hype
Founders
Daniel Nadler CEO
Harvard PhD; previously founded Kensho, a financial analytics firm acquired by S&P Global
Zachary Ziegler Co-founder
Machine learning researcher from Harvard
Reality · Working here
Signals & Risks
Editorial ✎
Good fit for
· Engineers/scientists who want to build products that genuinely shape clinical decisions — feedback here is real physician prescribing and diagnostic behavior, high-stakes and high-signal
· People who prefer 'slow trust, fast scale' dynamics — trust in medical settings builds slowly but compounds into a deep moat once earned
· Anyone genuinely into medical literature and evidence-based medicine — the core product distills massive volumes of papers and guidelines into answers doctors can act on
Not for
· People who like fast, loose iteration and tolerate ambiguous answers — medical contexts have zero tolerance for wrong answers, so engineering and eval rigor bars are very high
· Anyone uneasy about valuation-bubble dynamics or unwilling to work at the intensity implied by 4 rounds in 11 months
Ask in the interview
1. Valuation is up 12x in a year — internally, is that seen as fundamentals-driven, or as the market pricing in an 'AI + healthcare' narrative?
2. How is the ~30% US physician usage number defined and measured (active use, frequency)? What does retention and real paid conversion look like behind that figure?
3. As a product directly shaping clinical decisions, how does the company see its own role regarding medical liability and regulation (FDA / state medical boards)?
Data changelog
Community corrections → editorial review → applied, fully on the record
data as of 2026-01 · Source: Pulse2 (citing company funding announcement) ↗
data as of 2026-01 · Source: Pulse2 (citing company funding announcement) ↗
data as of 2026-01 · Source: Pulse2 (citing company funding announcement) ↗
data as of 2026-01 · Source: Pulse2 (citing company funding announcement) ↗
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