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This dataset covers 6,930 verified records spread across 79+ districts in Uttar Pradesh. 6,930 records carry a verified phone number and 2,426 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Ambedkar Nagar (1,399 listings), Kaushambi (700 listings), Auraiya (466 listings), Jhansi (350 listings), Varanasi (280 listings), Lalitpur (233 listings), Bahraich (200 listings), and Ghaziabad (175 listings).
Additional coverage spans Hapur (155), Sitapur (140), Mahoba (127), Lakhimpur Kheri (117), Jalaun (108), Amroha (100), Bareilly (93), Farrukhabad (87), Agra (82), Meerut (78), Azamgarh (74), Balrampur (70) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Ambedkar Nagar | 1,399 | 1,399 | 490 |
| Kaushambi | 700 | 700 | 245 |
| Auraiya | 466 | 466 | 163 |
| Jhansi | 350 | 350 | 123 |
| Varanasi | 280 | 280 | 98 |
| Lalitpur | 233 | 233 | 82 |
| Bahraich | 200 | 200 | 70 |
| Ghaziabad | 175 | 175 | 61 |
| Hapur | 155 | 155 | 54 |
| Sitapur | 140 | 140 | 49 |
| All districts (79) | 6,930 | 6,930 | 2,426 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Ambedkar Nagar | 1,399 | 1,399 | 490 |
| Kaushambi | 700 | 700 | 245 |
| Auraiya | 466 | 466 | 163 |
| Jhansi | 350 | 350 | 123 |
| Varanasi | 280 | 280 | 98 |
| Lalitpur | 233 | 233 | 82 |
| Bahraich | 200 | 200 | 70 |
| Ghaziabad | 175 | 175 | 61 |
| Hapur | 155 | 155 | 54 |
| Sitapur | 140 | 140 | 49 |
| Mahoba | 127 | 127 | 44 |
| Lakhimpur Kheri | 117 | 117 | 41 |
| Jalaun | 108 | 108 | 38 |
| Amroha | 100 | 100 | 35 |
| Bareilly | 93 | 93 | 33 |
| Farrukhabad | 87 | 87 | 30 |
| Agra | 82 | 82 | 29 |
| Meerut | 78 | 78 | 27 |
| Azamgarh | 74 | 74 | 26 |
| Balrampur | 70 | 70 | 25 |
| Etawah | 67 | 67 | 23 |
| Jaunpur | 64 | 64 | 22 |
| Kanpur Dehat | 61 | 61 | 21 |
| Shravasti | 58 | 58 | 20 |
| Kanpur | 56 | 56 | 20 |
| Siddharthnagar | 54 | 54 | 19 |
| Mathura | 52 | 52 | 18 |
| Sambhal | 50 | 50 | 18 |
| Rampur | 48 | 48 | 17 |
| Pilibhit | 47 | 47 | 16 |
| Prayagraj | 45 | 45 | 16 |
| Kushinagar | 44 | 44 | 15 |
| Kanpur Nagar | 42 | 42 | 15 |
| Bijnor | 41 | 41 | 14 |
| Shrawasti | 40 | 40 | 14 |
| Moradabad | 39 | 39 | 14 |
| Raebareli | 38 | 38 | 13 |
| Mainpuri | 37 | 37 | 13 |
| Hamirpur | 36 | 36 | 13 |
| Baghpat | 35 | 35 | 12 |
| Budaun | 34 | 34 | 12 |
| Aligarh | 33 | 33 | 12 |
| Gautam Buddha Nagar | 33 | 33 | 12 |
| Gonda | 32 | 32 | 11 |
| Deoria | 31 | 31 | 11 |
| Mirzapur | 30 | 30 | 11 |
| Amethi | 30 | 30 | 11 |
| Chitrakoot | 29 | 29 | 10 |
| Bulandshahr | 29 | 29 | 10 |
| Hathras | 28 | 28 | 10 |
| Saharanpur | 27 | 27 | 9 |
| Banda | 27 | 27 | 9 |
| Ballia | 26 | 26 | 9 |
| Sant Kabir Nagar | 26 | 26 | 9 |
| Fatehpur | 25 | 25 | 9 |
| Unnao | 25 | 25 | 9 |
| Barabanki | 25 | 25 | 9 |
| Lucknow | 24 | 24 | 8 |
| Kasganj | 24 | 24 | 8 |
| Bhadohi | 23 | 23 | 8 |
| Shahjahanpur | 23 | 23 | 8 |
| Pratapgarh | 23 | 23 | 8 |
| Chandauli | 22 | 22 | 8 |
| Etah | 22 | 22 | 8 |
| Kheri | 22 | 22 | 8 |
| Sultanpur | 21 | 21 | 7 |
| Muzaffarnagar | 21 | 21 | 7 |
| Firozabad | 21 | 21 | 7 |
| Ayodhya | 20 | 20 | 7 |
| Gorakhpur | 20 | 20 | 7 |
| Sonbhadra | 20 | 20 | 7 |
| Ghazipur | 19 | 19 | 7 |
| Allahabad | 19 | 19 | 7 |
| Shamli | 19 | 19 | 7 |
| Hardoi | 19 | 19 | 7 |
| Kannauj | 18 | 18 | 6 |
| Maharajganj | 18 | 18 | 6 |
| Basti | 18 | 18 | 6 |
| Mau | 16 | 16 | 6 |
| All districts (79) | 6,930 | 6,930 | 2,426 |
The Mortgage Lending Services database for Uttar Pradesh, India includes 6,930+ 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.
Sameera (IN) bought 1 day ago · Naseer (IN) bought 1 day ago · Ajay (IN) bought 2 days ago · Alaknanda (IN) bought 3 days ago · Nirmal (IN) bought 3 days ago
The Mortgage Lending Services database for Uttar Pradesh, India contains 6,930+ verified businesses as of 2026, each with phone, email, address, website and GPS coordinates. The full record count is shown on this page above.
The complete Mortgage Lending Services database for Uttar Pradesh, 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.
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.
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 mortgage lending services footprint in Uttar Pradesh, India.
Yes. The Mortgage Lending Services 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.
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.
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.
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.
Data2Sales AI's World Wide Data database for Uttar Pradesh, India consolidates 6,930+ 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.
Last Update:
Aug 08, 2026 02:32 AM
Published:
May 11, 2026 02:29 AM
Rows (Regular):
3,465
Rows (Extended):
6,930
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
