Install on Vercel – LogoAIpro Docs

Vercel Deployment: Deploy LogoAIpro to Vercel for easy, fast, and scalable hosting. Vercel provides automatic deployments, SSL certificates, and global CDN distribution.

Prerequisite: Make sure you've completed the How to push to GitHub guide before proceeding with Vercel deployment.

Step 1: Create Vercel Account

Go to vercel.com
Click "Sign Up" and sign in with GitHub
Authorize Vercel to access your GitHub account
Complete the onboarding process

Step 2: Import Project

In Vercel Dashboard, click "New Project" or "Add New..." → "Project"
Click "Import" next to your logo-ai-pro repository
Vercel will detect it's a Next.js project automatically

Step 3: Configure Project Settings

Framework Preset: Next.js (auto-detected)
Root Directory: ./ (root of repository)
Build Command: npm run build (default, keep as is)
Output Directory: .next (default, keep as is)
Install Command: npm install (default, keep as is)

Step 4: Configure Environment Variables

Add all environment variables from the Environment Variables page. Click "Environment Variables" in the project settings and add:

Required Environment Variables:

NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY - Clerk public key
CLERK_SECRET_KEY - Clerk secret key
CLERK_WEBHOOK_SECRET - Clerk webhook secret
DATABASE_URL - MongoDB connection string
NEBIUS_API_KEY - Nebius AI API key
NEXT_PUBLIC_STRIPE_PUBLISHABLE_KEY - Stripe public key
STRIPE_SECRET_KEY - Stripe secret key
STRIPE_WEBHOOK_SECRET - Stripe webhook secret
UPSTASH_REDIS_REST_URL - Upstash Redis URL
UPSTASH_REDIS_REST_TOKEN - Upstash Redis token
NEXT_PUBLIC_APP_URL - Your Vercel deployment URL (e.g., https://logo-ai-pro.vercel.app)

Important: Set NEXT_PUBLIC_APP_URL after the first deployment, using your actual Vercel domain URL.

Step 5: Deploy

Click "Deploy"
Wait for build to complete (takes 2-5 minutes)
Once deployed, Vercel will provide your production URL (e.g., https://logo-ai-pro.vercel.app)

Step 6: Post-Deployment Configuration

Update Environment Variables

Go to Project Settings → Environment Variables
Update NEXT_PUBLIC_APP_URL with your production domain
Redeploy to apply changes

Configure Webhooks

Update webhook URLs in external services:

Clerk: Update webhook URL to https://yourdomain.vercel.app/api/webhooks/clerk
Stripe: Update webhook URL to https://yourdomain.vercel.app/api/webhooks/stripe

Configure Custom Domain (Optional)

Go to Project Settings → Domains
Add your custom domain (e.g., logo-ai-pro.com)
Follow DNS configuration instructions
Update NEXT_PUBLIC_APP_URL with your custom domain

Important Notes

Vercel-Specific Considerations:

Function Timeout: Vercel has a 10-second function timeout on the Hobby plan. Some AI operations may exceed this limit. Consider AWS EC2 for longer-running operations.
File Size Limits: Vercel has a 50MB function size limit. Ensure your build stays under this limit.
Automatic Deployments: Every push to main branch triggers a new deployment automatically.
Preview Deployments: Pull requests get preview deployments automatically.
SSL Certificates: Vercel provides free SSL certificates automatically.

Limitations:

AI logo generation may exceed Vercel's 10-second timeout on some operations
For production with high traffic, consider AWS EC2 deployment instead
Monitor function execution time in Vercel Analytics

Monitoring & Analytics

Deployments: View all deployments in the Deployments tab
Analytics: Enable Vercel Analytics for performance monitoring
Logs: Check function logs in the Deployments → Functions tab

Troubleshooting

Build Fails

Check build logs for errors
Verify all environment variables are set
Ensure package.json has correct scripts

Runtime Errors

Check function logs for runtime errors
Verify API keys are correct
Check MongoDB connection string

Timeout Errors

AI operations may exceed 10-second limit
Consider upgrading to Vercel Pro plan for longer timeouts
Or deploy to AWS EC2 for unlimited execution time

Next Steps

After Deployment:

Configure Stripe webhooks
Configure Clerk webhooks
Test the application
Consider AWS EC2 for production (if you need longer execution times)

Alternative Deployment: For production use with heavy AI processing, consider deploying to AWS EC2 which offers better performance and no function timeout limitations.