⚡ BATCH ENGINE: UP TO 200 FILES (.XLSX, .XLS, .CSV, .PDF, .DOCX, .TXT)

Extract & Separate Mobiles, Landlines & Emails

Upload up to 200 files simultaneously (.xlsx, .xls, .csv, .pdf, .docx, .txt) or paste raw text. Automatically separates clean columns for Mobile Number, Country Code, Country Name, STD Code, and Email Address with deep validation and typo auto-detection.

Multi-Column Excel & CSV Export

150+ Indian STD & City Detection

240+ Global Country Codes

Word .docx & Multi-Page PDF Parser

Email Typo & Disposable Auto-Fixer

100% Client-Side Privacy

Drag & drop files here or click to browse

Select up to 200 files simultaneously (.xlsx, .xls, .csv, .pdf, .docx, .txt)

Supported: Excel (.xlsx, .xls), Comma/Tab Separated (.csv, .tsv), PDF Directories (.pdf), Word Documents (.docx), Plain Text (.txt)

Files in Queue 0 / 200 files

Auto-detect email typos (e.g. @gmial.com → @gmail.com) Map Indian STD codes to cities (e.g. 022 Mumbai, 0265 Vadodara) Deduplicate extracted records across files

Ready to analyze

Processing file 1 of 1... 0%

Extracted: 0 mobiles, 0 emails Speed: calculating...

India Mobiles (10-Digit)

Landlines (STD Codes)

International Numbers

Valid Emails

Typos Flagged

Files Processed

Download Clean Structured Data

How Accuracy & Multi-Column Splitting Works

📱 Mobile Number Splitting

10-digit Indian numbers starting with 6, 7, 8, or 9 are parsed, stripped of +91, 91, 0 prefixes, and structured into: Mobile Number (10 digits), Country Code (+91), Country Name (India), and STD Code (blank).

☎️ STD Code Landline Separation

Landlines written like 022-24331997, 1141545625, or 0135-2698884/5/6 are split into STD Code (e.g. 022), Landline Number, and City Name (e.g. Mumbai, Delhi, Ahmedabad, Vadodara) across 150+ mapped Indian cities.

🌍 240+ Global Dial Codes

International numbers with + country codes (e.g. +1 USA, +44 UK, +971 UAE, +49 Germany, +94 Sri Lanka, +998 Uzbekistan) are detected using official ITU prefix tables with country identification.

✉️ RFC Validation & Typo Fixer

Addresses are validated for RFC syntax, disposable domains (1500+ domains), and auto-corrected for common domain typos (e.g. @gmial.com → @gmail.com, .con → .com).