Building an AI SaaS with Next.js, FastAPI, and Dokploy
A solo developer shares the tech stack and architecture used to build an AI project, focusing on balancing performance, shipping speed, and server costs.
Why it matters
This article provides a practical example of how a solo developer can build a cost-effective, high-performance AI SaaS using a modern tech stack.
Key Points
- 1Used Next.js and Tailwind CSS for the frontend
- 2Leveraged FastAPI for the backend to handle AI inference tasks asynchronously
- 3Deployed the app on Hetzner Cloud using the open-source Dokploy platform
- 4Emphasized the importance of proper error handling when dealing with async AI generation
Details
The developer needed a tech stack that would allow them to move quickly on the frontend, handle heavy AI inference tasks smoothly on the backend, and keep hosting costs low. They chose Next.js and Tailwind CSS for the frontend, Python and FastAPI for the backend, and Hetzner Cloud with the Dokploy self-hosted PaaS for the infrastructure. The key benefits were the developer-friendly experience of Next.js, the asynchronous capabilities of FastAPI for AI tasks, and the cost savings of self-hosting with Dokploy. The biggest challenge was managing the async nature of AI generation, which required proper error handling on the frontend to handle timeouts and other issues.
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