AI Content Production Pipeline

Stable Diffusion and Image Generation

The visual generation stage uses fal.ai's infrastructure to run Stable Diffusion XL and Flux models at scale, producing high-resolution images that match the storyboard prompts generated in the scripting phase. Each frame is generated with consistent style parameters — aspect ratio, color palette, and artistic direction — ensuring visual coherence across the entire video. The system generates multiple candidate images per scene and uses a scoring algorithm to select the frame that best matches the narrative context.

Wan Video Model Integration

For scenes requiring motion, the pipeline integrates the Wan video generation model, which transforms static images into short animated clips with natural camera movement and subject motion. This bridges the gap between slideshow-style content and fully animated video, adding production value that dramatically increases viewer engagement and watch time. The Wan model excels at producing smooth transitions, subtle environmental effects, and character animations that bring static compositions to life.

ElevenLabs Voice Synthesis

Narration is generated through ElevenLabs' neural text-to-speech engine, which produces studio-quality voiceovers indistinguishable from professional voice actors. The system supports multiple voice profiles tuned to different content categories — authoritative tones for business and technology topics, conversational styles for lifestyle content, and energetic delivery for entertainment niches. Voice cloning capabilities allow channels to maintain a consistent narrator identity across their entire content library.

The narration module automatically segments the script into timed blocks, generating audio files with precise timestamps that the assembly engine uses to synchronize visual transitions with speech cadence. Pause insertion, emphasis marking, and pronunciation guides are embedded in the script format, giving the voice synthesis engine the context it needs to deliver natural, engaging narration without manual audio editing.

Orchestration Engine

The Node.js orchestration layer manages the complete pipeline lifecycle from URL ingestion to YouTube upload. Each stage emits structured events that downstream stages consume, creating a decoupled architecture where individual components can be upgraded, replaced, or scaled independently. The orchestrator handles retry logic with exponential backoff, provider rate limiting, and cost tracking per video to maintain predictable unit economics.

Assembly and Post-Production

The video assembly stage combines generated images, animated clips, narration audio, background music, and text overlays into a cohesive final render. Transition effects are selected algorithmically based on scene mood and pacing, with Ken Burns motion applied to static images to maintain visual interest. The system generates multiple thumbnail candidates using composition rules optimized for YouTube click-through rates, then selects the highest-scoring option based on contrast, text readability, and emotional impact metrics.

YouTube Channels

Scalable channel operations with consistent content quality. Transform any niche into a content machine with automated production that maintains brand consistency across hundreds of videos in a content library.

B2B Marketing

Content production for marketing teams and agencies who need to turn thought leadership articles, whitepapers, and case studies into engaging video content at scale without production crews or studio time.

Education and Training

Rapid content creation for educational platforms and corporate training programs. Convert documentation, course materials, and technical guides into engaging video tutorials with professional narration.

Pipeline entrypoint and orchestration

Core pipeline logic and stages

Automation helpers and utilities

Guides, runbooks, and roadmap