Case Study: Bond achieves 2x order fulfillment and scalable operations with MongoDB Atlas

Delivering Thoughtfulness at Scale Using MongoDB Atlas & AWS

Bond is a New York–based gifting company that uses proprietary machine‑learning algorithms and a fleet of handwriting robots to generate personalized, handwritten notes. Rapid customer growth exposed limits in their original MySQL on Amazon RDS backend — read‑heavy traffic (≈1,000 reads/sec) caused write‑consistency and operational problems, forcing engineers to spend more time on datastore troubleshooting than on product development.

Bond migrated first to MongoDB and then to a managed MongoDB Atlas deployment on AWS, moved their stack toward Node.js and Python for ML, and adopted tools like the Connector for Apache Spark. The change stabilized IOPS, enabled a machine‑data analytics platform to optimize robot performance, and supported ML‑driven customer insights — allowing Bond to fulfill twice as many orders in six months as they had in the previous two years and refocus engineering on innovation.

Bond

Sam Broe

Chief Product Officer