Next.js has become the go-to framework for building modern web applications, and with the introduction of the AI SDK, integrating AI capabilities has never been easier. This comprehensive guide will walk you through building scalable AI applications.

Why Next.js for AI Applications?

Next.js has emerged as the premier framework for building production-ready AI applications, offering a powerful combination of performance, scalability, and developer experience. With React Server Components (RSC), you can stream AI responses efficiently, delivering real-time interactions without sacrificing performance. The framework's flexible runtime options let you leverage edge functions for low-latency AI interactions or serverless functions for complex computational workloads—all on a per-route basis.

Vercel AI SDK: Your AI Integration Powerhouse

The Vercel AI SDK solves the pain of provider inconsistency by offering a unified interface across OpenAI, Anthropic, Mistral, and more through its Language Model Specification. Built-in streaming support with hooks like useChat() and useCompletion() simplifies real-time AI responses, while the streamUI() function enables streaming React components directly from server to client. The SDK's support for Server Actions means you can call AI models directly from your frontend with type-safe, server-side functions.

Practical Tips for Production

When deploying AI applications to production, implement rate limiting on API routes to manage costs and prevent abuse. Edge caching with Redis or Vercel KV can dramatically reduce latency for frequently requested AI completions. Next.js 15's Rust-based tooling delivers up to 30% faster refresh times in development, making iteration smoother. Remember that edge functions have a 1-4 MB code size limit but offer zero cold starts—perfect for lightweight AI preprocessing. For complex AI workloads, stick with serverless functions that can handle unpredictable traffic patterns through automatic scaling.