Maxun – Open-Source No-Code Web Data Extraction Platform

Hacker News

Hey Everybody, We are thrilled to open source Maxun today. Maxun is an open-source no-code web data extraction platform. It lets you build custom robots for data scraping in just a few clicks. Maxun lets you create custom robots which emulate user actions and extract data, while handling dynamic parts like pagination and scrolling. Maxun also lets you turn websites to REST APIs and Spreadsheets. We also support a feature called BYOP (Bring Your Own Proxy) which lets you connect your own anti-bot infrastructure and save huge $$$. Would love to hear use-cases & feedback. Github : https://github.com/getmaxun/maxun Please join our community: - Github : https://github.com/getmaxun/maxun - Discord : https://discord.gg/NFhWDCdb - Twitter : https://x.com/maxun_io Thank you, Team Maxun

Visit product View on Hacker NewsOct 30, 2024

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

77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

38%38% predicted probability of success on AppSumo, 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 · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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