Me

Meter – Web scraping that syncs only what changed

Hacker News

Meter – Web scraping that syncs only what changed

I spent a ton of time writing custom scrapers for different use cases, and I got tired of following the same pattern. Recently, I spent tons of time firing up custom scrapers and syncing data for a RAG app I built. I built Meter to solve both of these issues: it makes creating a fast, CSS selector based scraper easy and it makes tracking content changes simple for use cases where data needs to stay in sync. It's free for now - you can test it out by clicking "Get Started" and going to the dashboard and testing the scraping out. I'd love any feedback!

Visit product View on Hacker NewsDec 28, 2025

Actual performance

2points

1comments

Did not reach leaderboard

Launch Intel predictions

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

78%78% 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 · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

61%61% 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 · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

45%45% 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

18%18% 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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