Deployment Overview

Once you've built and optimized your AI application, Empromptu provides multiple deployment options to get your application live. Deploy directly to hosting platforms or download for self-hosting.

What you'll learn ⏱️ 3 minutes

  • Available deployment options

  • When to use each deployment method

  • Prerequisites for deployment

  • What gets deployed with your application

Deployment Options

Deploy to Netlify

Best for: Quick hosting with minimal setup

  • One-click deployment to Netlify's platform

  • Automatic HTTPS and global CDN

  • Easy domain configuration

  • Requires: Netlify account

Deploy to GitHub

Best for: Version control and collaboration

  • Push your application to a GitHub repository

  • Enable GitHub Actions and Pages if desired

  • Full version control for your AI application

  • Requires: GitHub account

Download Project

Best for: Self-hosting and custom deployments

  • Download complete application as zip file

  • Host on your own infrastructure

  • Full control over deployment environment

  • Requires: Web hosting solution

Accessing Deployment Options

Deployment buttons appear in the Builder interface when you're working on your project:

  • Deploy to Netlify (green button)

  • Deploy to GitHub (dark button)

  • Download Project (purple button)

All three options are available once you've built your AI application.

What Gets Deployed

Complete Application Files

Your deployment includes everything Empromptu generated:

  • Application code: All necessary source files

  • Dependencies: package.json and required libraries

  • Configuration: Setup and environment files

  • AI capabilities: Complete AI functionality included

File Structure Examples

Depending on your application, you might see:

  • package.json: Project dependencies and scripts

  • app.tsx: Main application file (if React/TypeScript)

  • Configuration files: Environment and setup files

  • Assets: Any resources your application needs

Prerequisites

Before Deploying

For Netlify deployment: Active Netlify account For GitHub deployment: Active GitHub account with repository access For Download: Web hosting solution for self-hosting

Account Setup

Set up your accounts before attempting deployment:

  • Create accounts on your preferred platforms

  • Ensure you have necessary permissions

  • Have authentication ready for the deployment process

Deployment Process Overview

General Workflow

  1. Build your application in the Builder interface

  2. Optimize performance using LLMOps tools (optional but recommended)

  3. Click your preferred deployment button

  4. Complete authentication and configuration steps

  5. Your AI application goes live

Authentication Flow

Each deployment option will:

  • Request authentication to the target platform

  • Guide you through necessary configuration steps

  • Handle the deployment process automatically

  • Provide you with the live application URL or files

Choosing the Right Deployment Method

Deploy to Netlify

Choose when:

  • You want the fastest path to a live application

  • You need reliable hosting with minimal setup

  • You prefer managed infrastructure

  • You want automatic HTTPS and CDN

Deploy to GitHub

Choose when:

  • You want version control for your AI application

  • You plan to collaborate with a team

  • You want to integrate with GitHub's ecosystem

  • You prefer GitHub Pages hosting

Download Project

Choose when:

  • You have existing hosting infrastructure

  • You need full control over the deployment environment

  • You want to host on-premise or in private cloud

  • You plan to integrate with existing systems

Enterprise On-Premise Options

Available for enterprise customers: On-premise deployment with continued optimization capabilities

  • Deploy to your own infrastructure

  • Maintain connection to Empromptu for optimization

  • Keep data and processing local while leveraging cloud optimization tools

Post-Deployment Considerations

Monitoring and Updates

  • Continue optimization: Use LLMOps tools even after deployment

  • Monitor performance: Track real user interactions

  • Update as needed: Redeploy when you make improvements

  • Scale appropriately: Consider traffic and performance needs

Ongoing Optimization

Your deployed application can continue to improve:

  • End User Inputs: Monitor real usage patterns

  • Performance tracking: See how optimization translates to production

  • Iterative improvement: Deploy updates based on real-world performance

Next Steps

Ready to deploy your AI application?

  • Deploy to Netlify: Quick hosting with automatic configuration

  • Deploy to GitHub: Version control and repository management

  • Download Project: Self-hosting and custom deployment options

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