Your teams have automated the software lifecycle: code generation, reviews, testing, continuous integration, and deployment. With AI agents, code and development environments are multiplying at an unprecedented rate. The data layer, however, remains largely static.

Creating a database environment, synchronizing it, resetting it, or providing a usable copy often remains a lengthy and cumbersome operation. This lag becomes the weak link in agent workflows: each branch, each agent, and each additional test ends up depending on a data infrastructure that is not provisioned at the same speed.

This session demonstrates how database cloning and branching enables the provisioning of isolated environments on demand, in seconds, and gives agents the same experimental capability that developers already have for their code.