Case study
EhudAI
AI-Powered Content Creation Studio
EhudAI is an end-to-end AI-powered platform for movie and content production that brings story creation, character development, visual generation, and video production into a single workflow.
View live project- Role
- Full-Stack Developer
- Timeline
- Multi-phase development with continuous feature enhancement
- Stack
- Next.js, TypeScript, Flask, PostgreSQL, OpenAI GPT-4, DALL-E
The Challenge
Content creators and filmmakers typically juggle disconnected tools for writing, design, and video editing. This fragmented workflow is expensive, slow, and breaks creative momentum. EhudAI was built to unify these steps under one roof with AI doing the heavy lifting.
What I Built
The platform combines a Next.js frontend with a Flask backend, orchestrating multiple AI services through a unified interface.
Unified AI Workflow
Rather than switching between separate tools, users move fluidly from story outline to finished video. The platform maintains context across every stage — a character created during writing carries its visual identity into image and video generation.
Dual AI Interaction Modes
The platform offers two distinct ways to work with AI. A conversational chat mode handles content editing and writing assistance, while an agent mode makes structural changes to scenes, characters, and story elements directly in the database.
Real-Time Collaboration
Built with Liveblocks, the collaborative editor supports multiple users working on the same project simultaneously with live cursors, conflict resolution, and version history.
Multi-Modal Generation Pipeline
The system chains AI services together — text descriptions become images through DALL-E or Flux AI, static images become dynamic video through RunwayML or Google Veo, and story outlines transform into formatted screenplays.
Technical Highlights
The backend manages orchestration across multiple AI providers, each with different rate limits, response formats, and capabilities. A service abstraction layer handles provider switching and error recovery transparently.
Media storage runs through AWS S3 with progressive loading to handle the large video files that the generation pipeline produces. Stripe powers the subscription billing system with usage-based pricing tiers.
Impact
The platform reduces content creation time significantly by eliminating tool-switching and manual handoffs between creative stages. Users go from concept to produced content within a single session, with AI assistance at every step.
Technologies Used: Next.js, TypeScript, Flask, PostgreSQL, OpenAI GPT-4, DALL-E, RunwayML, Flux AI, Google Veo, Kling AI, Liveblocks, Stripe, AWS S3, Tailwind CSS, Radix UI
Live Demo: EhudAI Platform
