I built an open-source alternative to Formspree. Here's the plan to monetize it.
A friend of mine builds websites for small businesses. Every client needs a contact form. Every time it's the same problem -- Formspree's free tier runs out, clients don't want to pay $20/mo, so he ends up hacking together some webhook-to-Google-Sheets workaround.
I kept hearing this from other devs too. And the problem is so stupidly simple -- receive a POST request, save it, send a notification. That's it. That's the whole product.
So I built FormTo. Self-hosted form backend. You set the action attribute on your HTML form, run docker compose up -d, and submissions show up in a dashboard. Notifications go to email, Telegram, Slack, or any webhook.
Where I'm at right now:
Just open-sourced it on GitHub (AGPL-3.0)
$0 revenue, 0 users (launched this week)
Solo dev, no funding, no co-founder
Built with React, Fastify, PostgreSQL, Caddy
The monetization plan:
The open-source version is fully featured and always will be. No artificial limits, no "upgrade to unlock" tricks.
The money comes from a hosted cloud version. Same product, but I handle the server, backups, HTTPS, updates. Target audience: freelancers and small agencies who want FormTo but don't want to manage a VPS. Thinking $9-15/mo per workspace.
Basically the same playbook as Plausible, Umami, Cal.com -- free self-hosted, paid cloud.
Why I think this can work:
Formspree charges $20/mo and up. Basin, Formcarry -- similar range.
The self-hosted crowd is big and growing. If even 1% of self-hosters convert to cloud because they get tired of maintenance, that's the business.
Form backends are boring infrastructure. People pay for boring infrastructure because it just needs to work.
What I'm figuring out:
Where to find the first 10 paying users for the cloud version
Whether to launch cloud on its own domain or keep everything under formto.dev
How to grow GitHub stars without being spammy about it
Would love to hear from anyone who's done the open-source + paid cloud model. What worked, what didn't?
Nice approach.
One thing I’ve been running into while building is that AI tools don’t always agree when reviewing code.
Sometimes one flags an issue, another says it’s fine.
It makes debugging and validation a bit tricky.
Curious if you’ve seen that too while building this.