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I built a free AI tool that picks your SaaS tech stack based on budget

I built a free AI tool that picks your SaaS tech stack based on budget

by rupatiwari25·Feb 22, 2026·6 points·4 comments

AI Analysis

MidCrowd PleaserSolve My Problem

Budget-aware stack recommendations, but advice guides and ChatGPT already recommend stacks better.

Strengths
  • Accounts for per-seat and per-user costs (Clerk, Linear)—real insight most generic advice ignores
  • Clean UX with PDF export and shareable links; no-code-only toggle is thoughtful for non-technical founders
  • Free, zero-friction entry—generates results without account or signup
Weaknesses
  • Solves a subjective problem poorly: startup stacks depend on product maturity, risk tolerance, and hiring plans—an AI form can't replace narrative reasoning
  • Direct competition from ChatGPT, Indie Hackers threads, and curated stack guides—recommendation engines succeed on trust and pattern recognition, not feature count. No clear moat.
Category
Target Audience

Startup founders, solo developers deciding on tools; non-technical founders building SaaS

Similar To

ChatGPT · Indie Hackers threads · Roadmap.sh

Post Description

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.

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