Dailymotion's Journey to Crafting the Ultimate Content-Driven Video Recommendation Engine with Qdrant Vector Search - Qdrant

Dailymotion implemented a content-based video recommendation engine using Qdrant. They process video metadata (title, tags, description, transcript) into MUSE embeddings and use Qdrant for fast and accurate similarity search. This resulted in a significant reduction in recommendation processing time (from hours to minutes) and a 3x increase in interaction and CTR for recommended videos, particularly for fresh and low-signal content. Qdrant's capabilities in handling high-dimensional data, scalability, and metadata filtering were crucial for this implementation.