Case Study: Document360 boosts AI accuracy and search speed with MongoDB Vector Search

Document360 boosts AI answer rates to 91% with MongoDB

Document360, a knowledge base platform under Kovai.co, needed its AI assistant to reliably answer complex, multi-part user questions. The challenge was that using a separate vector database for semantic search would require complex data syncing and threaten their intricate access controls and compliance, which were already deeply integrated within their primary MongoDB database.

By implementing MongoDB Vector Search on Atlas, Document360 created a unified hybrid search platform that performed both keyword and semantic searches natively. This solution, combined with Voyage AI for reranking, boosted the AI's answer rate to 91% and baseline response accuracy to 96%. The results included a 70% increase in user 'likes', a 30% reduction in 'dislikes', and lightning-fast retrieval times of 2-4 milliseconds, which fueled explosive user adoption and trust.

Document360