— CASE 03 / RAG OVER VIDEO · VIVANSH INFOTECH
COURSE
BUILDER.
Search 10,000 clips, let Gemini direct, narrate with ElevenLabs, render on serverless. End-to-end training course in one pass.
1w → 10mPer course
10KSource clips indexed
99%Time reduction
$2Per course · serverless
— THE PIPELINE
RAG, BUT THE
CHUNKS ARE
10-SECOND
VIDEO CLIPS.
Source videos cut into 10-second clips with FFmpeg, each analyzed by Gemini 2.5 Pro for visual content, embedded with Cohere embed-english-v3, indexed in Milvus.
At generation time the user uploads a course doc; AI returns an outline, then in parallel: RAG retrieves 80-100s of candidate clips per ~60s lesson, Cohere reranks, Gemini selects + orders + writes narration in a single inference.
Heavy rendering — cut, merge, overlay, audio mix, transitions — offloaded to AWS Lambda with FFmpeg, so the EC2 app server never feels it.
FASTAPIMILVUSCOHEREGEMINI 2.5ELEVENLABSFFMPEGAWS LAMBDAS3SAM CLI
— WANT THE FULL STORY?