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This dataset covers 2,780 verified records spread across 79+ districts in Uttar Pradesh. 2,780 records carry a verified phone number and 973 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Bijnor (561 listings), Firozabad (281 listings), Hapur (187 listings), Kushinagar (140 listings), Bareilly (112 listings), Jaunpur (94 listings), Rampur (80 listings), and Gorakhpur (70 listings).
Additional coverage spans Azamgarh (62), Kanpur Dehat (56), Chandauli (51), Mathura (47), Sultanpur (43), Meerut (40), Etawah (37), Pilibhit (35), Agra (33), Sambhal (31), Kanpur Nagar (30), Amroha (28) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Bijnor | 561 | 561 | 196 |
| Firozabad | 281 | 281 | 98 |
| Hapur | 187 | 187 | 65 |
| Kushinagar | 140 | 140 | 49 |
| Bareilly | 112 | 112 | 39 |
| Jaunpur | 94 | 94 | 33 |
| Rampur | 80 | 80 | 28 |
| Gorakhpur | 70 | 70 | 25 |
| Azamgarh | 62 | 62 | 22 |
| Kanpur Dehat | 56 | 56 | 20 |
| All districts (79) | 2,780 | 2,780 | 973 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Bijnor | 561 | 561 | 196 |
| Firozabad | 281 | 281 | 98 |
| Hapur | 187 | 187 | 65 |
| Kushinagar | 140 | 140 | 49 |
| Bareilly | 112 | 112 | 39 |
| Jaunpur | 94 | 94 | 33 |
| Rampur | 80 | 80 | 28 |
| Gorakhpur | 70 | 70 | 25 |
| Azamgarh | 62 | 62 | 22 |
| Kanpur Dehat | 56 | 56 | 20 |
| Chandauli | 51 | 51 | 18 |
| Mathura | 47 | 47 | 16 |
| Sultanpur | 43 | 43 | 15 |
| Meerut | 40 | 40 | 14 |
| Etawah | 37 | 37 | 13 |
| Pilibhit | 35 | 35 | 12 |
| Agra | 33 | 33 | 12 |
| Sambhal | 31 | 31 | 11 |
| Kanpur Nagar | 30 | 30 | 11 |
| Amroha | 28 | 28 | 10 |
| Sonbhadra | 27 | 27 | 9 |
| Mainpuri | 26 | 26 | 9 |
| Farrukhabad | 24 | 24 | 8 |
| Allahabad | 23 | 23 | 8 |
| Hamirpur | 22 | 22 | 8 |
| Kanpur | 22 | 22 | 8 |
| Varanasi | 21 | 21 | 7 |
| Auraiya | 20 | 20 | 7 |
| Lalitpur | 19 | 19 | 7 |
| Jalaun | 19 | 19 | 7 |
| Bahraich | 18 | 18 | 6 |
| Mahoba | 18 | 18 | 6 |
| Gautam Buddha Nagar | 17 | 17 | 6 |
| Barabanki | 17 | 17 | 6 |
| Jhansi | 16 | 16 | 6 |
| Lakhimpur Kheri | 16 | 16 | 6 |
| Sitapur | 15 | 15 | 5 |
| Shamli | 15 | 15 | 5 |
| Hardoi | 14 | 14 | 5 |
| Shahjahanpur | 14 | 14 | 5 |
| Shravasti | 14 | 14 | 5 |
| Maharajganj | 13 | 13 | 5 |
| Banda | 13 | 13 | 5 |
| Sant Kabir Nagar | 13 | 13 | 5 |
| Bhadohi | 12 | 12 | 4 |
| Ayodhya | 12 | 12 | 4 |
| Unnao | 12 | 12 | 4 |
| Ambedkar Nagar | 12 | 12 | 4 |
| Balrampur | 11 | 11 | 4 |
| Gonda | 11 | 11 | 4 |
| Muzaffarnagar | 11 | 11 | 4 |
| Mau | 11 | 11 | 4 |
| Moradabad | 11 | 11 | 4 |
| Raebareli | 10 | 10 | 4 |
| Ghazipur | 10 | 10 | 4 |
| Etah | 10 | 10 | 4 |
| Pratapgarh | 10 | 10 | 4 |
| Prayagraj | 10 | 10 | 4 |
| Kannauj | 10 | 10 | 4 |
| Shrawasti | 9 | 9 | 3 |
| Ballia | 9 | 9 | 3 |
| Siddharthnagar | 9 | 9 | 3 |
| Baghpat | 9 | 9 | 3 |
| Aligarh | 9 | 9 | 3 |
| Mirzapur | 9 | 9 | 3 |
| Hathras | 9 | 9 | 3 |
| Kaushambi | 8 | 8 | 3 |
| Basti | 8 | 8 | 3 |
| Deoria | 8 | 8 | 3 |
| Bulandshahr | 8 | 8 | 3 |
| Kheri | 8 | 8 | 3 |
| Budaun | 8 | 8 | 3 |
| Saharanpur | 8 | 8 | 3 |
| Lucknow | 8 | 8 | 3 |
| Amethi | 8 | 8 | 3 |
| Kasganj | 7 | 7 | 2 |
| Fatehpur | 7 | 7 | 2 |
| Chitrakoot | 7 | 7 | 2 |
| Ghaziabad | 7 | 7 | 2 |
| All districts (79) | 2,780 | 2,780 | 973 |
The English Speaking Institutes database for Uttar Pradesh, India includes 2,780+ 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.
Rosey (IN) bought 3 hours ago · Jobin (IN) bought 1 day ago · Kirti (IN) bought 2 days ago · Raghavan (IN) bought 4 days ago · Aayushman (IN) bought 5 days ago
The English Speaking Institutes database for Uttar Pradesh, India contains 2,780+ 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 English Speaking Institutes 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 english speaking institutes footprint in Uttar Pradesh, India.
Yes. The English Speaking Institutes 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.
This World Wide Data list covers 2,780+ verified records operating in Uttar Pradesh, India. Every entry is compiled by the Data2Sales AI engine from multiple verified sources, de-duplicated against our master index, and refreshed each month — saving sales, marketing, and research teams the manual cleanup normally needed before outreach.
Last Update:
Aug 08, 2026 02:32 AM
Published:
May 11, 2026 02:28 AM
Rows (Regular):
1,390
Rows (Extended):
2,780
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
