Start here: the deployment decision tree
Deciding where to deploy ai generated apps is simpler than it looks once you sort your app by what it needs. Ask three questions: does it need a backend or database, does anything have to run all the time, and where was it built? A static frontend with no server logic belongs on a static host. Anything with an API, a database, or always-on processes needs a VPS with full root access. Apps built inside Hostinger AI Builder can simply stay on Hostinger hosting.
This guide walks through all three paths honestly, including the one where Hostinger is not the answer. The common thread: AI tools generate the code, but deployment is still engineering. Expect to clean up generated code, move secrets out of the source, and attach a real database before anything production-facing goes live.
Option 1: static hosts for frontend-only apps
If your AI tool produced a static site, plain HTML, CSS, and JavaScript with no server code, static hosts are the fastest and cheapest deployment on earth. Netlify, Vercel, and Cloudflare Pages all accept a git push or drag-and-drop upload, issue free SSL, and serve your site from a global CDN within minutes. Generous free tiers cover portfolios, landing pages, and prototypes comfortably.
The limits are architectural, not just pricing. Static hosts cannot run a persistent backend, hold long-lived connections, or execute scheduled jobs; the moment your app needs a real API or database writes beyond serverless functions, you have outgrown this tier. Custom domains work on all three, and migration later is painless since your code stays in your own repository.
Option 2: a VPS for backends and databases
When your app needs a backend, a database, or always-on processes, a VPS is the honest answer. You get full root access on a Linux server, install Docker, and run your frontend, API, and database as containers you control completely. A Hostinger VPS with KVM virtualization handles this well: pick a plan with headroom for your database, deploy with Docker Compose, and put Cloudflare or a reverse proxy in front for HTTPS.
The trade is responsibility. A VPS is self-managed: you handle OS updates, firewall rules, backups, and security patching, and AI-generated code often needs a cleanup pass before it deserves public traffic. For the database layer, pair the VPS with a managed Postgres like Supabase rather than self-hosting everything; our Supabase on a VPS walkthrough covers that setup step by step.
Option 3: staying inside Hostinger AI Builder
The path of least resistance is not moving at all. Apps and sites generated in Hostinger AI Website Builder, which absorbed the Horizons app builder in August 2026, deploy onto Hostinger hosting with no export step, no server config, and no separate deploy pipeline. For marketing sites, MVPs, and internal tools built in the builder, this is the fastest route from prompt to public URL.
Know the ceiling. You stay inside the Hostinger ecosystem, backend flexibility is bounded by what the builder supports, and AI credit pricing is unpublished, so heavy iterative building costs are hard to forecast. If your app outgrows the builder, export the code while the project is small; migrations get harder, not easier, with size.
Deciding where to deploy ai generated apps that need managed services
Here is where Hostinger is not the answer. If your app needs a managed database with point-in-time recovery, autoscaling under traffic spikes, compliance certifications, or a team deploying many times a day, a raw VPS adds operational burden you should not carry. Managed platforms like Railway, Render, Fly.io, or the major cloud providers exist precisely for that middle ground between static hosts and bare servers.
This is not a knock on VPS hosting; it is about matching operational appetite to the product stage. A solo founder validating an idea is well served by a VPS. A funded team with uptime obligations should pay for managed infrastructure and spend engineering time on the product instead of patching servers at 2 a.m.
A practical middle path exists too: keep the database managed while the app itself runs on your VPS, which removes the hardest operational piece without abandoning the cost advantage. Many teams run this hybrid for years before anything forces a bigger move.
The pre-launch checklist and the renewal reality
Whatever path you chose, run this checklist before announcing anything. Export the full code to your own git repository so you are never locked to a builder. Move every API key and secret into environment variables; AI tools love hardcoding them. Attach a real database with backups, connect a custom domain with HTTPS enforced, and take a full snapshot you can restore. Document the rollback steps alongside the checklist so a bad deploy is a ten-minute revert, not a midnight rebuild.
Then price the second year, not the first. Static host free tiers can tighten, VPS plans renew above intro rates (check our renewal breakdown), and builder subscriptions climb. Deployment is day one of operations, not the finish line; budget the ongoing cost with the same care you gave the build.
| Your app needs | Static host | VPS | AI Builder hosting |
|---|---|---|---|
| Frontend only | Ideal, free tiers | Overkill | Fine for simple sites |
| Backend or API | Not supported | Full control via Docker | Limited to builder features |
| Database | External service needed | Self-host or managed | Built-in options |
| Always-on processes | No | Yes | No |
| Management effort | Low | High, self-managed | Lowest |
| Custom domain + HTTPS | Included free | You configure it | Included |
VPS KVM 2
24-month plan, paid upfront
Renews at $14.99/mo
- 2 vCPU + 8 GB RAM
- 100 GB NVMe storage
- 8 TB bandwidth
- Full root access
- n8n one-click template available
FAQ
Yes, if the app has a backend. Export the code from the AI tool to your own repository, then deploy it on the VPS with Docker: one container for the frontend, one for the API, and a managed or self-hosted database. Static-only exports can go to Netlify or Vercel instead, which is simpler and cheaper.
A static export on a free static-host tier costs nothing for frontend-only apps. For apps with backends, a small VPS is the cheapest flexible option, since one server can host the app, API, and database together. Staying inside the AI builder you already pay for is cheapest of all when it fits.
Not strictly, but it helps enormously. Docker lets you package the exact environment your AI tool assumed, which kills most it-works-on-my-machine deployment failures. If Docker feels like too much, staying in your AI builder or using a managed platform removes that layer entirely.
You can export the generated code, but expect a migration project rather than a one-click move: you will wire up your own hosting, domain, and backend services on the new platform. Export early while the project is small, and keep your own git repository as the source of truth from day one.
Do not ship with the toy database your AI tool scaffolded. Use a managed Postgres service like Supabase for reliability and backups, connected over a private network or with strict firewall rules. Store connection strings in environment variables, never in the generated source code.
Usually not. AI-generated code commonly ships with hardcoded secrets, missing input validation, no rate limiting, and outdated dependencies. Treat the output as a strong first draft: review authentication flows, update dependencies, add backups, and run a basic security pass before exposing anything to the public internet.