
Dmand AI
The Healthcare Sales Intelligence & Outbound Platform
AI & Machine Learning·Marketing·Sales & CRM·Data & Infrastructure
1 person waiting for launch day
About
Selling into US healthcare fails on data. Horizontal databases link people to a company by email domain, so a nurse manager at a satellite clinic shows up under a health system 300 miles away, or not at all. Healthcare data vendors know the facilities but not the people, and none of them run outreach.
Dmand AI is built on the complete US healthcare universe. Every health system, IDN, hospital, division, physician group, operating org and outpatient site sits in an accurate org hierarchy, with 7M+ HCPs and 8M+ executives affiliated at the site level. Contact coverage for emails, direct dials and LinkedIn is 40% higher than any other tool or data vendor.
On top of the data: 360-degree profiles of every HCP and executive, network discovery that surfaces who already knows your prospect, AI research columns, multi-channel sequences, a unified inbox, and enterprise-grade access controls, with Salesforce, HubSpot, Slack, Google Workspace and Outlook integrations.
Database Scale
- 7M+ HCPs
- 8M+ Health Executives
- 850K+ Sites of Care
- 250K+ Healthcare Organizations
- 120K+ Physician Groups
Org Hierarchy
Every entity is placed in a parent-child tree: site of care → hospital or operating org → division → health system → IDN. 6.2K+ hospitals and 50K+ satellite units are modeled with full hierarchy, including sites like SNFs, ASCs, solo clinics and others. People are linked by org tree, not by email domain.
Coverage Universe
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Health Systems and IDNs, Hospitals (acute, critical access, specialty, academic medical centers)
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Physician Groups and Medical Groups, Independent Practices
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Ambulatory Surgery Centers (ASCs), Imaging Centers, Urgent Care
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Clinics: FQHCs, Rural Health Clinics, Retail Clinics, Renal Dialysis Facilities, Behavioral Health
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Post-Acute and Long Term Care: Skilled Nursing Facilities, Assisted Living, Home Health, Hospice
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Accountable Care Organizations (ACOs), Clinically Integrated Networks, GPOs
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HCPs: Physicians, Nurses, Advanced Practice Providers, Allied Health Professionals
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Executives and decision makers across clinical, operational, technology, finance, quality and population health functions
Affiliations
Physician-to-site, physician-to-medical group, physician-to-employer and executive-to-org affiliations, mapped against the org hierarchy and continuously refreshed. Includes primary and secondary practice locations.
360-Degree Profiles
Every HCP and executive profile brings together: procedures and patient volumes, clinical trials, publications, education and training history, colleagues, affiliations with any site, medical group or employer, work history, associations and boards, certifications, open payments, prescriptions, contact channels, and organizational context (hierarchy, service lines, EHR, beds, workforce, financials, ownership).
Network Discovery
Relationship graph between the people you already know and the people you want to reach: current coworkers (same and different specialties), past colleagues, shared academic institutions (medical degree, residency, fellowship, training), co-publishers, and clinical trial co-investigators. Turns cold outreach into a referral path.
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Launch NowFounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
Now that anyone can build any software they want, knowledge and product is no longer the moat. The moat is your distribution... someone goes out and builds Creator Buddy 2.0 the exact same app in 5 seconds but they have 10 followers — I'm going to outsell them in circles.
Distribution beats product when anyone can clone your app in hours
Alex made $100K in 15 minutes not because his product was technically superior, but because he had spent 3 years building an audience of people who trusted him. In the AI era where anyone can replicate an app quickly, the launch advantage belongs entirely to whoever owns distribution. Building in public for years before the launch was the actual product.
one that I really like is time to first sale which is basically how long does it take for a mentor uh that joins Mentor Crews to get their first Mente uh and that's like a really crucial metric... you have liquidity so how much of you or how many of our mentors currently work with a Mente how much of our supply is actually on use right now
Track marketplace-specific metrics SaaS founders ignore: time-to-first-sale, liquidity, GMV
MRR alone hides the structural health of a marketplace. Add: (1) time-to-first-sale per supplier — how fast new mentors get booked; (2) liquidity — % of supply actively earning right now; (3) GMV — total transaction volume flowing through, not just your cut; (4) demand:supply ratio. These are the leading indicators of marketplace health. If time-to-first-sale rises, your supply is outpacing demand and you need to brake supply onboarding.
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