Workflow · media · workflow
Vimeo builds a RAG-powered video Q&A system for knowledge-sharing content
Video viewers who lack time to watch full recordings need a way to extract information from video content in natural language; knowledge-sharing videos like meetings and lectures are particularly hard to query without watching them entirely.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Transcript ingestion
Each video uploaded to Vimeo is already transcribed via automatic closed captions, providing the textual input for the Q&A system.
Tools used
RAGLLMvector databaseChatGPT 3.5
Outcome
Vimeo built a video Q&A system using RAG that answers questions in natural language, surfaces playable video moments, and suggests related questions; experiments show the transcript alone is sufficient to answer most important questions for knowledge-sharing videos.
Grounding & classification
Source type: technical build writeup
22 fields verified against source quotes.
conversational aiknowledge searchragspeech to textsummarizationmeeting recordingbuilder submittedmetric backednamed customerproduction runtime claimedtools describedworkflow describedmediasoftwareaccuracy improvementtechnical build writeuprag answering