I built a free AI tool that picks your SaaS tech stack based on budget
Hey HN, I kept seeing the same question asked over and over in startup communities: "What tech stack should I use for my SaaS?" The answers were always scattered, opinionated, and never accounted for budget or team size. So I built appstackbuilder.com — you tell it your monthly budget, app type, team size, and skill level, and it recommends a full stack (auth, database, hosting, payments, analytics, etc.) with actual pricing for each tool. A few things that make it different from generic advice: - It accounts for team size when calculating costs (e.g. Clerk charges per user, Linear charges…
What it does
In the maker’s words, at launch
Hey HN, I kept seeing the same question asked over and over in startup communities: "What tech stack should I use for my SaaS?" The answers were always scattered, opinionated, and never accounted for budget or team size. So I built appstackbuilder.com — you tell it your monthly budget, app type, team size, and skill level, and it recommends a full stack (auth, database, hosting, payments, analytics, etc.) with actual pricing for each tool. A few things that make it different from generic advice: - It accounts for team size when calculating costs (e.g. Clerk charges per user, Linear charges per seat — most stack guides ignore this) - You can toggle "no-code only" if you're a non-technical founder - It shows you 2–3 alternatives per category, not just one option - You can export the full stack as a PDF or share a link - It's completely free, no account required Under the hood: Next.js, Supabase, and Gemini for the recommendations. The tool database has ~80+ tools across categories with real pricing data I manually verified. What I'm still figuring out: - How to keep pricing data fresh as tools change plans frequently - Whether to add a "stack score" based on community usage data - If the no-code recommendations are actually good (I'm a developer, so I'd love feedback from non-technical founders specifically) Would love brutal feedback, especially if the recommendations feel off for your use case.
Does the same job
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