This dataset covers 191,354 verified records spread across
35+ states in India.
191,354 records carry a verified phone number and
82,486 include a business website — directly usable for
outreach, segmentation, and CRM import.
The highest-density states are
Maharashtra (23,522 listings), Uttar Pradesh (22,480 listings), Gujarat (15,119 listings), Madhya Pradesh (12,012 listings), Tamil Nadu (10,808 listings), Rajasthan (9,080 listings), Karnataka (8,743 listings), and Punjab (8,535 listings).
Additional coverage spans
Andhra Pradesh (7,780),
Kerala (6,193),
Telangana (6,171),
Haryana (6,058),
Jharkhand (5,205),
Bihar (5,070),
Chhattisgarh (3,948),
Delhi (3,458),
West Bengal (3,306),
Odisha (2,684),
Uttarakhand (2,558),
Assam (2,354)
, plus 15 more states.
Coverage in India — by state
Total rows:191,354With mobile:191,354With website:82,486
The Hospitals database for India includes 191,354+ verified businesses with company name, address, city, state, phone, email, website and GPS coordinates. The file is delivered as a CSV ready for CRM import or BI analysis.
Kunti (IN) bought 1 day ago
·Jayshree (IN) bought 2 days ago
·Kirti (IN) bought 4 days ago
·Gayatri (IN) bought 1 week ago
·Prerna (IN) bought 1 week ago
How to use this data
Account-based marketing — target every hospitals firm in India with personalised plays.
Investor reports — anchor TAM/SAM numbers in India hospitals to a verifiable list, not industry estimates.
Retention monitoring — flag hospitals accounts in India that have moved or closed since last contact.
Frequently asked about this dataset
How many businesses are in the Hospitals database for India?
The Hospitals database for India contains 191,354+ verified businesses as of 2026, each with phone, email, address, website and GPS coordinates. The full record count is shown on this page above.
Where can I download a Hospitals database for India?
The complete Hospitals database for India is available on this page from Data2Sales AI as an instant CSV download. Every record carries verified contact details and is delivered immediately after checkout.
What fields are included in the Hospitals dataset?
Each record includes: Business name, Street address, City, State / Region, Postal code, Country, Phone number, Email address and more. The file is delivered as a UTF-8 CSV that opens in Excel, Google Sheets or any standard CRM importer.
How accurate is the Hospitals data for India?
Every record is cross-referenced across public business registries, Google Maps and licensed directory partners before it ships. Closed businesses, disconnected phones and duplicates are stripped on every monthly refresh, so the dataset reflects the live hospitals footprint in India.
Is the Hospitals dataset updated regularly?
Yes. The Hospitals dataset is rebuilt on a rolling 30-day cycle. New entrants come in through registrar filings; closures are detected from negative signals and dropped before export.
Can I use the Hospitals data for marketing and outreach?
Yes — the dataset is licensed for commercial use after purchase. Common use cases include cold outbound, geo-targeted advertising, market research, supplier sourcing and territory planning. Only publicly listed business contact information is included.
What format do I receive the Hospitals database in?
You receive a UTF-8 encoded CSV. It opens in Excel, Google Sheets, Power BI, Looker Studio and every major CRM (HubSpot, Salesforce, Zoho, Pipedrive). XLSX is available on request.
How quickly can I download the dataset after purchase?
Within 30 seconds of successful payment. The CSV is generated fresh from the live database at purchase time. You also get 7 days of unlimited re-downloads from a secure link sent to your email.
About the Hospitals Database in India
Data2Sales AI's World Wide Data database for India consolidates 191,354+ verified records into a single, verified contact list. The engine crosses multiple sources — official websites, business registries, social profiles, licensed directories — and validates each record monthly, so your sales pipeline starts with accurate data instead of a spreadsheet of guesses.