Telegram-Archive – Own your chat history

Hacker News

Hey, I'm Sergio, the dev behind Telegram-Archive I built Telegram-Archive because I wanted complete control over my chat history, no matter what might happen (i.e. my account gets locked, or Telegram changes policies, etc.) It's composed of a backup and a viewer. It has been evolving for some time and it's more complex than that, so you can, for example, archive and share public channels. Feel free to check the features. I think the project is still in its infancy, but I hope you can bring your expertise and suggestions too. Built with Python, FastAPI, Telethon, and Vue. GPLv3 licensed.

Visit product View on Hacker NewsJan 29, 2026

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

30%30% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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