LoomScribe

Video content is global, but language isn't. Creators, educators, and businesses produce video in one language and lose 80% of their potential audience. Professional dubbing costs thousands per video and takes weeks. Existing automated tools produce robotic output that sounds nothing like the original speaker.

The challenge was building a platform that could transcribe accurately, translate naturally, and generate dubbed audio that preserves the speaker's vocal characteristics — all through a simple upload interface that anyone could use.

LoomScribe combines multiple AI models in a single pipeline: OpenAI Whisper for speech-to-text transcription, GPT-4 for natural translation that preserves tone and context, and ElevenLabs voice synthesis for dubbed audio that sounds like the original speaker in a new language.

The architecture handles video processing asynchronously — users upload a file, the system extracts audio, runs it through the AI pipeline, and delivers results without blocking the interface. A queue-based system ensures reliability under load.

Key architectural decisions: provider abstraction so we can swap AI models without rewriting business logic, aggressive caching of repeated transcriptions, and a webhook-based notification system so users don't have to wait on a loading screen.