Build an AI Podcast Clipping SaaS: Python, Next.js, AWS, Stripe, Tailwind, TS, Modal, Inngest

you'll build a SaaS application that converts full podcasts into viral short-form clips ready for YouTube Shorts or TikTok. The tool uses different AI models to transcribe the video, automatically detect the most engaging moments in podcasts and create clips cropped to the active speaker's face. You'll learn how to build a complete production-ready SaaS with user authentication, a credit-based payment system using Stripe, and background processing queues to handle user load. All services used in this project are free, so you won't have to pay anything to follow along. We'll use technologies such as Next.js 15, React, Typescript, Tailwind CSS, ShadCN, Auth.js, Python, FastAPI, Stripe, Modal, Inngest, S3 on AWS, and more

Features:

• 🎬 Auto-detection of viral moments in podcasts (stories, questions, etc.)

• 🔊 Automatically added subtitles on clips

• 📝 Transcription with m-bain/whisperX

• 🎯 Active speaker detection for video cropping with Junhua-Liao/LR-ASD

• 📱 Clips optimized for vertical platforms (TikTok, YouTube Shorts)

• 🎞️ GPU-accelerated video rendering with FFMPEGCV

• 🧠 LLM-powered viral moment identification with Gemini 2.5 Pro

• 📊 Queue system with Inngest for handling user load

• 💳 Credit-based system

• 💰 Stripe integration for credit pack purchases

• 👤 User authentication system

• 📱 Responsive Next.js web interface

• 🎛️ Dashboard to upload podcasts and see clips

• ⏱️ Inngest for handling long-running processes

• ⚡ Serverless GPU processing with Modal

• 🌐 FastAPI endpoint for podcast processing

• 🎨 Modern UI with Tailwind CSS & Shadcn UI

• codebase: https://www.devblog.blog/store/ai-podcast-clipping-saas-codebase-mm5o3m7e

• video: https://youtu.be/PeFZcvWucoU?si=wdpsphSMPxxSnn_M