Building AI applications with Next.js: a practical architecture
A practical guide to structuring AI applications with Next.js — server components, API routes, streaming, and secure LLM calls.
Next.js is a strong choice for building AI applications because it gives you server-side rendering, route handlers, and streaming out of the box.
Architecture at a glance
- Server Components render most UI
- Route Handlers proxy LLM calls so API keys stay on the server
- Streaming responses make AI output feel fast
- MySQL or Postgres store application data
Keep secrets on the server
Never call an LLM provider from the browser. Create a route handler that holds the API key in an environment variable and proxies the request.
Streaming
Use the Web Streams API to stream tokens to the client. Users see responses appear instantly instead of waiting for the full completion.
Retrieval (RAG)
- Store your content as vectors in a vector database
- Embed the user question at request time
- Retrieve relevant chunks and pass them as context
- Send the final prompt to the LLM
Evaluation
Track real interactions. Sample conversations and grade them on helpfulness, accuracy, and safety. Build a small evaluation dataset from your own domain.
Security checklist
- Validate and sanitise all inputs
- Rate limit public endpoints
- Never log API keys or prompt contents
- Add human approval for destructive actions
Work with our engineers on your next AI application.