This content originally appeared on DEV Community and was authored by Tach Yolo
Building an AI Image Generation SaaS with Next.js and TypeScript
I recently launched aipose.ai, an AI-powered image and video generation platform offering 20+ creative tools. Here's how I built it and the key decisions I made.
What It Does
The platform provides various AI-powered features:
- AI Headshot Generator with 100+ professional styles
- Image Editing: Background removal, object removal, image expansion, recoloring
- Portrait Tools: Outfit changer, expression modifier, hairstyle changer, makeup generator
- Video Generation: Text-to-video and image-to-video
- Special Effects: Baby predictor, age progression, gender swap, and more
Tech Stack
Core Technologies
// Next.js 15 with App Router for great SEO
export async function generateMetadata(): Promise<Metadata> {
return {
title: "AI Image & Video Generator",
description: "Create stunning AI images and videos",
keywords: ["AI image generator", "AI video generator"],
};
}
Why This Stack?
- Next.js 15: Server components, excellent SEO, built-in optimizations
- TypeScript: Type safety across the entire codebase
- Turborepo: Monorepo for better code organization
- Shadcn UI + Tailwind: Fast, customizable UI development
- Prisma: Type-safe database access
- Better-auth: Modern authentication
- Stripe: Payment processing
Monorepo Architecture
poseai-app/
├── apps/web/ # Next.js application
├── packages/
│ ├── ai/ # AI service integrations
│ ├── api/ # API routes
│ ├── database/ # Prisma schema
│ ├── payments/ # Stripe integration
│ └── ...
This structure keeps code modular and reusable across different parts of the application.
Key Features
1. AI Headshot Generator with 100+ Styles
The standout feature is the headshot generator with styles ranging from "Corporate Business" to "Cyberpunk":
export interface GenerateHeadshotParams {
imageData: string;
style: HeadshotStyle; // 100+ options
backgroundType: BackgroundType;
quantity: number;
}
const HEADSHOT_STYLES = [
{
name: "Corporate Business",
style: "corporate-business",
prompt: "Professional corporate headshot with business suit..."
},
{
name: "Cyberpunk",
style: "cyberpunk",
prompt: "Futuristic cyberpunk portrait with neon lighting..."
},
// ... 98 more styles
];
2. Modular AI Service Design
Each AI feature is a self-contained module:
// packages/ai/lib/ai-headshot.ts
export async function generateHeadshotPack(
params: GenerateHeadshotParams
): Promise<GeneratedHeadshot[]> {
const prompt = buildHeadshotPrompt(params.style, params.backgroundType);
return await generateImageWithGemini({ ...params, prompt });
}
3. Credit System
Simple but effective credit-based pricing:
await prisma.$transaction(async (tx) => {
const user = await tx.user.findUnique({ where: { id: userId } });
if (user.credits < amount) {
throw new Error('Insufficient credits');
}
await tx.user.update({
where: { id: userId },
data: { credits: { decrement: amount } }
});
});
Challenges & Solutions
Image Processing Performance
Problem: Large image uploads causing timeouts
Solution: Client-side compression before upload
AI Service Reliability
Problem: Third-party AI services can fail
Solution: Retry logic with exponential backoff
Cost Control
Problem: AI API calls are expensive
Solution: Credit system + rate limiting + usage monitoring
Performance Optimizations
- WebP images with Next.js Image component
- Dynamic imports for heavy components
- API route caching
- CDN for static assets
Deployment
# Environment management with dotenv-cli
pnpm dev
# Stripe webhooks (local testing)
stripe listen --forward-to localhost:3000/api/webhooks/payments
# Database management
npx prisma studio
Lessons Learned
- Monorepo pays off: Initial setup takes time, but organization improves dramatically
- Prompt engineering matters: Well-crafted prompts improve AI output quality 10x
- User experience is critical: Loading states, clear errors, mobile optimization
- Monitor costs: AI APIs are expensive - implement usage limits and monitoring
Results
The platform now serves users with:
- 20+ AI-powered tools
- 100+ headshot styles
- Multi-language support
- Responsive design
- Smooth payment flow
What's Next
- Batch processing
- More AI models
- Public API for developers
- Mobile apps
- Community features
Conclusion
Building an AI SaaS is challenging but rewarding. Key takeaways:
- Choose battle-tested tech (Next.js + TypeScript)
- Keep services modular
- Optimize for performance early
- Monitor costs carefully
- Prioritize UX
Check out aipose.ai to see it in action!
Questions? Drop them in the comments below!
This content originally appeared on DEV Community and was authored by Tach Yolo
Tach Yolo | Sciencx (2025-11-12T23:38:52+00:00) Building an AI Image Generation SaaS with Next.js and TypeScript. Retrieved from https://www.scien.cx/2025/11/12/building-an-ai-image-generation-saas-with-next-js-and-typescript-2/
Please log in to upload a file.
There are no updates yet.
Click the Upload button above to add an update.