UsageFlow – API usage metering, rate-limits and usage reporting

Hacker News

I’m launching UsageFlow, a simple tool for API owners who want automatic API usage metering and full control over their endpoints — all without any hassle. With just a few lines of code, the UsageFlow SDK gives you: Automatic discovery of API endpoints User identification Usage metering Rate-limits and automatic blocking Reporting usage events to your existing billing or metering system Supports: Go (Gin), Python (FastAPI, Flask), Node.js (Express, Fastify, NestJS) Perfect for AI APIs or SaaS platforms that want to scale fast — focus on building your product while UsageFlow handles usage tracking automatically. No developer skills required to: Update usage rules Apply limits Report usage Everything works with a few clicks — your entire usage platform is in your hands, instantly. I’m opening this for first testers. If you run an API and want to try UsageFlow, comment below or DM me — I will create your account and get you started in minutes. Learn more at: https://usageflow.io

Visit product View on Hacker NewsNov 20, 2025

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

81%81% 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.

Indie HackersIH features products with proven revenue · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created

48%48% 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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

22%22% 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

19%19% 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.

Correct prediction on native model

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