Potarix – AI-Powered Web Scraping and Data Extraction

Hacker News

Hey guys, I wanted to show what we have been working on for the last few weeks. We have done data extraction/web scraping for the last few months, and we built this internally to help us. However, clients requested a SAAS tool, so here it is! You guys can test it out here (app.potarix.com). Everyone who signs up gets 5$ credits. Scraping each page takes up $0.10 of your credits. You are not charged for unsuccessful scrapes! We launched last week, and our platform was super buggy. We initially launched without the concept of "jobs" in our product, so every time you wanted to scrape a platform, you would have to wait 5 minutes on one screen to get your results. Something is bound to happen in those 5 minutes, so the task would fail for some unknown reason. Looking ahead, we built stuff in-house that we would love to include in the SAAS platform shortly. We have built functionality to click, type, scroll, etc. on the page. AI also tends to be wrong sometimes, so we created a tweakable script in the backend to control the agent's actions. That way, you are in control and can bring the script to 100% accuracy. We have also seen people battling to build infrastructure for their large-scale scraping projects. We wanna autonomously let folk set up parallelization and choose the infra for their project so everything is scraped as quickly and succinctly as possible from the SAAS. If any of these future features sound interesting, feel free to book some time, and we can discuss how we can help you with these now!

Visit product View on Hacker NewsDec 16, 2024

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

94%94% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

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

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month, way, para · Missing: mobile apps, ios, personal

41%41% 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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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