EliteSaaS – Self-Contained SaaS Starter (Auth, Billing, Email, Launch)

Hacker News

Hi HN, I got tired of rebuilding the same boilerplate for every side project — auth, billing, dashboards, waitlists, email flows, SEO metadata, launch pages… you know the drill. Most “SaaS starters” still require stitching together a bunch of external tools — Zapier, Intercom, Mailchimp, analytics, Stripe, etc. That ends up being fragile and expensive. So I built EliteSaaS to solve that. What’s included: • Auth, user management, password reset • Stripe subscriptions (recurring billing + coupons) • Admin dashboard, user table, impersonation • Built-in email flows and campaign manager (uses Resend) • Basic analytics • SEO + OpenGraph generator • Product Hunt + social launch content generator • Optional waitlist mode with invite codes Tech stack: • Next.js • Tailwind • Supabase • Resend • Vercel (deploy-ready) I built this for myself originally, and now I’m using it to spin up side projects fast without losing momentum on boring setup. Site: https://www.elitesaas.dev Happy to answer questions or get feedback!

Visit product View on Hacker NewsJun 29, 2025

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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

85%85% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

82%82% 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

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

44%44% 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

36%36% 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, recurring, subscription · Missing: arr, mrr, revenue

27%27% 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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