49M IG Emails Scraped in 2024—System Failed, Need Help

Hey community, I’m not sure if this is the right place for Instagram scraping, but a friend recommended this forum to me. I’ve been running a big operation in 2024, scraping over 49 million emails from Instagram, making around $100k per month. Unfortunately, my scraping system stopped working, and my numbers are starting to drop without fresh data coming in. The data i already have is useless for me, as what im doing only works once. I don’t speak English well, so I’m using Google Translate to communicate, and I prefer written messages. If anyone can help me with scraping or has some advice, I’d really appreciate it! Let’s collaborate.

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Really sorry to hear about this. I’ve been doing the same for a couple of years now and I believe I can help you with this situation. I have a database of over 90M on Instagram and we have a rescraping/updating functionality that scrapes 2M+ per day. Add me on Telegram so we can talk more? @borisigscraper

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How are you making on scraping emails, you scrape and sell them?

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We are building a huge databaset that has instagram+youtube+twitter+tiktok+snapchat+onlyfans data for all creators out there. Currently the DB is at ±70M

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What is the exact Instagram failure symptom and last successful timestamp? Run one previously working target beside one current target, with only one variable changed, and say where it stops: profile discovery, page access, email-field extraction, or writing the result to storage. Also note any account, proxy, environment, or parser change.

  1. Send the exact Instagram failure symptom and the last successful timestamp, including timezone.

  2. Reproduce it with one previously working target and one current target. Keep the same worker, account, proxy, environment, and parser; change only the target.

  3. Mark the first failed state: profile discovery → page access → email-field extraction → result storage.

  4. Report every recent change to account state, proxy routing, runtime/environment, or parser version/configuration. That comparison identifies the changed component without guessing at the root cause.