Top of funnel
Screener
One page. The questions an investor asks first, answered with one line of evidence each. Red flags and green signals before you commit time.
- ROV score
- Key strengths and risks
- Team profile
- Sector and stage
Healthcare-specific due diligence · deal platform
The only deal platform that verifies every claim to its source
Both sides of the table, one matching engine — dimension-by-dimension fit with plain-English reasons, built on verified research, not scraped lists.
Request early access. Accounts open by invitation until launch.
—i
profiled investors
—i
of 50 dimensions compared per match
—
i
ROV-scored startups
—i
engine agrees with real portfolios
—
i
fit scores computed
—
i
facts from SEC filings
1See your matchesSign in and your dashboard ranks the other side of the table for you, with the reasons spelled out.
2Open a reportEvery scored company carries a verified report. Members open it after signing in.
3Ask for a data roomOn a company's profile, ask the founder to open their data room to your fund.
What theDealStream is
A two-sided pipeline for healthcare deals. If you run a startup, you get a ranked list of the investors whose mandate actually fits your company — stage, sector, check size — with the reasons spelled out, plus verified research you can hand to any of them. If you invest, you get a deal feed matched to your mandate, every company scored against cited evidence, the gaps flagged, and the likely co-investors for each deal. Same engine, both sides of the table.
Browse companies
Every healthcare startup on the platform — category, stage, ROV score, evidence level.
Browse investors
Every fund on the platform — type, stated focus, portfolio size.
Founder or investor? Request early access,
or sign in to see your matches.
Reports
One report for each stage of your funnel
Each level is built on the one before it. Every figure in every level is traced to the page it came from.
Pipeline
Scorecard
The ROV score opened up, pillar by pillar, with the source for every input and a sources document you can hand to a committee.
- Everything in the screener
- Four pillars, every metric scored
- Clinical and regulatory path
- Competitive landscape
- Sources document
Decision
Full due diligence
The long report: reimbursement, unit economics, regulatory path, exit map and a red-flag register, each item cited.
- Everything in the scorecard
- Reimbursement landscape
- Ranked diligence questions
- Exit and acquirer map
- Red-flag register
The score
The Warner-Starke Return on Value score
ROV scores a health or life science company 0 to 10 on four pillars. Each pillar is a set of named metrics, and each metric's input is traced to a cited source. It is a company-quality score, not a fit score. Fit is computed separately, for each fund.
Built by healthcare investment operators for healthcare deals: clinical evidence, the regulatory path and the payer landscape are scored on their own terms, not folded into a generic growth model.
The four pillars
Financial ValueMarket, payer dynamics, reimbursement, capital efficiency
Medical ImpactPatient outcome potential, disease burden, evidence maturity
Team and PeopleFounder-market fit, clinical leadership, advisory depth
Innovation and TechnologyNovelty, IP strength, regulatory path clarity, trial data quality
TrueRead™
every number, traced to the page that says it
TrueRead is the rule this whole site runs on: a number only appears here if we can show you the exact page that says it. Every funding amount, score input, and team fact links to its original source — press article, SEC filing, or the company's own site — so you can check any claim yourself in one click.
How a fact gets onto this site
Anagram — Series A · $9.1M
a line from an actual scorecard
cited to
techcrunch.com · 2020-03-03
"Software for out-of-network billing for healthcare providers
raises $9.1 million"
If the page does not say what our sentence says, the
sentence changes or it goes. Where we have no source, the row says so.
Founder documents stay home: data-room files are read on our own machines
and never reach a public AI service. How TrueRead works →
Why the databases disagree
what copying looks like
Most startup data products copy each other. When the copies disagree, there is no way to know which number is real — that is the problem TrueRead exists to fix.
$13.5Mvs$53.5M
one PitchBook page,
two answers — its funding table against its own FAQ
(opened 2026-08-07).
One database page, two different totals, same company, same day.
Health and life science
Built for the parts of healthcare that generic tools get wrong
Clinical validation, the regulatory path and payer reimbursement are scored by people who have worked inside them.
Digital healthBiotech and pharmaMedical deviceDiagnostics
Life science toolsCare deliveryMental and behavioral healthNeuro
Wellness and consumer healthPayer and adminOncologyCardiovascular
Women's healthRegenerative medicineAnimal, Ag and Industrial Bio
What decides each sector, and what we score →
Team
Built by people who have run healthcare deals
Operators, investors and clinical leaders. The people who wrote the scoring rules read the reports.
Stop guessing. Start knowing.
Accounts open by invitation until launch. Tell us who you are and we will be in touch by email.
—
On record
Loading…
Your pipeline
Loading…
Your profile
Investors that fit best
How to read Match % and Evidence
Match % is mandate fit, not company quality — a strong company can still show a low match if it doesn't fit what this fund invests in. Evidence is two things: the letter grades the fund's own data (A filings, B our research, C self-reported, D inferred); the word is how much of the comparison we could score. Thin evidence caps the tier even when the match looks high. Verified marks rows whose data comes from filings or our research with enough coverage and a Strong or Possible fit; verified rows rank first, then Strong before Possible, then the number. Your own unverified inputs are named once above the list, not in every row. Full methodology →| # | Investor | Match ⇅i | Tier ⇅i | Evidence ⇅i | Primary gapi |
|---|
Your fund: —
How to read Fit % and Evidence
Fit % is mandate match, not company quality — a 7.9-ROV company can rank below a 6.8 that actually fits your mandate. Evidence is two things: the letter grades the company's own data (A filings, B our research, C self-reported, D inferred); the word is how much of the comparison we could score. Thin evidence discounts the ranking and caps the tier. Your own unverified inputs are named once above the list, not in every row. Full methodology →New prospects matching your mandate
— verified companies first, Strong before Possible, then by fit to what this fund says (and its
actual investments show) it wants, with any portfolio companies you
already hold that also rank here kept in the list and marked
"Already invested."
| # | Startup ⇅i | ROV ⇅i | Raising ⇅i | Last raise ⇅i | Fit ⇅i | Tier ⇅i | Evidence ⇅i | Primary gapi |
|---|
Your plan
| Name ⇅ | Category | Stage | ROV score ⇅ | Evidence level |
|---|
| Name ⇅ | Type | Stated focus | Portfolio | Form D amount |
|---|