This dataset covers 14,650 verified records spread across
79+ districts in Uttar Pradesh.
14,650 records carry a verified phone number and
5,128 include a business website — directly usable for
outreach, segmentation, and CRM import.
The highest-density districts are
Lakhimpur Kheri (2,958 listings), Jaunpur (1,479 listings), Azamgarh (986 listings), Sonbhadra (739 listings), Mathura (592 listings), Sant Kabir Nagar (493 listings), Bareilly (423 listings), and Allahabad (370 listings).
The Industrial Companies database for Uttar Pradesh, India includes 14,650+ 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.
Chameli (IN) bought 2 hours ago
·Ghanshyam (IN) bought 6 hours ago
·Tejaswani (IN) bought 7 hours ago
·Monin (IN) bought 11 hours ago
·Sunita (IN) bought 14 hours ago
How to use this data
Inbound enrichment — match form fills against the industrial companies list to enrich Uttar Pradesh, India leads instantly.
Distribution planning — overlay industrial companies pins onto your fulfilment map for Uttar Pradesh, India.
Pipeline reporting — surface industrial companies pipeline coverage in Uttar Pradesh, India by city and state in your sales dashboards.
Frequently asked about this dataset
How many businesses are in the Industrial Companies database for Uttar Pradesh, India?
The Industrial Companies database for Uttar Pradesh, India contains 14,650+ 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 Industrial Companies database for Uttar Pradesh, India?
The complete Industrial Companies 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.
What fields are included in the Industrial Companies 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 Industrial Companies data for Uttar Pradesh, 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 industrial companies footprint in Uttar Pradesh, India.
Is the Industrial Companies dataset updated regularly?
Yes. The Industrial Companies 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 Industrial Companies 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 Industrial Companies 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 Industrial Companies Database in Uttar Pradesh, India
Data2Sales AI's World Wide Data database for Uttar Pradesh, India consolidates 14,650+ 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.