Building Real-Time AI Features in SaaS: WebSockets vs Server-Sent Events

Real-Time AI: What Users Expect in 2025

Users who've interacted with ChatGPT expect streaming AI responses — not a spinner that freezes for 10 seconds then dumps text. Real-time AI features (streaming, live updates, collaborative editing) are now table stakes for AI SaaS products.

Server-Sent Events (SSE): Best for AI Streaming

SSE is a one-way, HTTP-based protocol — perfect for AI text streaming. The server pushes data to the client, the client reads it. No setup overhead, works through proxies, supported natively in Next.js API routes.

The Vercel AI SDK uses SSE under the hood with toDataStreamResponse(). Your AI chat endpoint streams tokens to the frontend as they're generated, giving users the responsive ChatGPT experience.

WebSockets: Best for Bi-Directional Real-Time

WebSockets enable full-duplex communication — both client and server can send messages at any time. Use WebSockets for: live collaboration (multiple users editing simultaneously), real-time notifications, AI agent progress updates, and multiplayer features.

In Next.js, WebSocket servers run outside the HTTP lifecycle. Use a dedicated WebSocket server (Socket.IO on Railway) or a managed service (Ably, Pusher, Supabase Realtime).

Implementation: AI Streaming with SSE

// API Route: app/api/chat/route.ts
import { streamText } from 'ai';
import { openai } from '@ai-sdk/openai';

export async function POST(req: Request) {
  const { messages } = await req.json();
  const result = streamText({
    model: openai('gpt-4o'),
    messages,
  });
  return result.toDataStreamResponse(); // Streams SSE to client
}

Decision Matrix