Case Study: ElevenLabs achieves scalable AI voice innovation with MongoDB

ElevenLabs scales to $600M ARR with MongoDB

ElevenLabs, an AI voice technology company, faced a challenge scaling its enterprise products because its legacy database lacked native free-text search. This limitation forced engineers to build and maintain a complex secondary index store with custom synchronization code, draining valuable time and resources. To overcome this, they turned to MongoDB Atlas on Google Cloud.

By migrating to MongoDB, ElevenLabs consolidated its data layer, eliminating the need for separate search stores and fragile sync code. The solution from MongoDB provided built-in text querying capabilities and a flexible document model that natively handled their diverse data needs. This resulted in a stable data foundation that powered hyper-growth, driving the company to $600 million in annual recurring revenue and enabling it to seamlessly support millions of autonomous voice and chat agents globally.

ElevenLabs