Case Study: MishiPay reduces queue times and scales retail self-scanning with MongoDB Atlas

MishiPay doubles recurring revenue with MongoDB Atlas

MishiPay, a UK-based retail technology startup, faced the challenge of scaling its self-scanning payment app to support rapid international growth. Their system needed to process millions of inventory items and complex transactions in real-time, requiring a highly available and flexible database solution that could integrate diverse retailer data formats without a glitch. To build the foundation for this, they turned to MongoDB and its product MongoDB Atlas.

By implementing MongoDB Atlas, MishiPay gained a scalable, multi-cloud database service that provided the resilience and flexibility needed for their expansion. The solution enabled them to seamlessly handle over 200,000 transactions monthly, double recurring revenues, and onboard new retail clients within two weeks. MongoDB's technology ensured real-time processing and system uptime, which were essential for MishiPay to accelerate its vision of creating a new, streamlined retail ecosystem.

MishiPay