Case Study: Syncly accelerates customer feedback analytics with MongoDB Atlas Vector Search

Syncly speeds feedback analytics 10x with MongoDB

Syncly, a customer feedback analytics startup, faced scaling challenges as its manual method for semantic analysis of Voice of Customer data became inefficient. The server workload from calculating similarities between embedding vectors grew with their customer base, hampering performance. To manage this vector data effectively, they turned to MongoDB and adopted its Atlas Vector Search product.

By implementing MongoDB Atlas Vector Search, Syncly automated its similarity analysis and integrated vector search directly into its existing MongoDB Atlas platform. This solution delivered performance gains of more than 10 times faster than manual processing, significantly reduced server load and cloud costs, and streamlined development. The results allowed Syncly to deliver faster, more insightful analytics to its customers, improving both service efficiency and customer satisfaction.

Syncly