Deploy AI Models on Vercel

Vercel provides serverless infrastructure perfect for deploying lightweight AI models and API endpoints.

Prerequisites

• Vercel account
• Vercel CLI installed
• Next.js project (recommended)
• Model API keys (OpenAI, Anthropic, etc.)

Deployment Options

1. Serverless Functions

Deploy AI inference as serverless API routes:

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

export async function POST(req: Request) {
  const { messages } = await req.json()
  
  const result = await streamText({
    model: openai('gpt-4'),
    messages,
  })
  
  return result.toUIMessageStreamResponse()
}

2. Edge Functions

For lower latency:

export const runtime = 'edge'

export async function POST(req: Request) {
  // Your AI logic here
}

3. Using Vercel AI SDK

npm install ai @ai-sdk/openai

import { generateText } from 'ai'
import { openai } from '@ai-sdk/openai'

const { text } = await generateText({
  model: openai('gpt-4'),
  prompt: 'What is AI?',
})

Environment Variables

Add in Vercel Dashboard or CLI:

vercel env add OPENAI_API_KEY
vercel env add ANTHROPIC_API_KEY

Deploy

vercel deploy --prod

Monitoring

• Use Vercel Analytics
• Enable Web Vitals tracking
• Monitor function execution time
• Track error rates

Cost Optimization

• Use edge functions for lower costs
• Implement caching strategies
• Set function timeouts appropriately
• Monitor bandwidth usage

Production Checklist

• [ ] Set up environment variables
• [ ] Configure custom domain
• [ ] Enable analytics
• [ ] Set up error tracking
• [ ] Implement rate limiting
• [ ] Configure CORS
• [ ] Add authentication
• [ ] Set up monitoring alerts