ReadyKit – Superfast SaaS Starter with Multi-Tenant Workspaces

Hacker News

Hi HN! I've been building ReadyKit, an open-source SaaS boilerplate that handles all the hard parts: multi-tenant workspaces, Stripe billing, OAuth + MFA authentication, and a production-ready stack. Built with Python/Flask, PostgreSQL, Redis, and Vue 3, it's designed for indie makers and teams who want to ship SaaS products fast. Clone, configure your OAuth and Stripe keys, and you're running in 5 minutes. Features include automatic query scoping for workspace isolation, audit logs, role-based access, and a modern UX kit. MIT licensed and free forever. GitHub: https://github.com/level09/readykit

Visit product View on Hacker NewsNov 30, 2025

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Actual performance

121points

35comments

Made the leaderboard

Launch Intel predictions

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

72%72% 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

68%68% 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

52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% 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

29%29% predicted probability of success on TrustMRR, 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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