Case Study: LekoTech achieves sub-two-second search and faster sales with MongoDB Vector Search on Atlas

LekoTech cuts search latency from 35 seconds to under 2 seconds with MongoDB

LekoTech, an automotive startup digitizing the global auto parts market, faced a significant challenge with its search system. The company needed to manage complex metadata for millions of parts but was experiencing search latencies of up to 35 seconds on its previous platform, which hindered its mission to promote a circular economy. To handle high data variability and scale rapidly, LekoTech turned to MongoDB for a solution.

By implementing MongoDB Atlas and MongoDB Vector Search, LekoTech consolidated its search strategy onto a unified data platform. This solution cut search latency to under two seconds and enabled intuitive, natural-language queries for users. The measurable impact was substantial, with some auto dismantler customers doubling their sales within months. The performance and scalability provided by MongoDB were also critical in helping LekoTech become an official eBay partner, achieving €2 million in sales on the platform in a single year.

LekoTech