Agents need more than a model and a prompt. They need retrieval, persistent memory, access to operational data, observability and reliable deployment across the full pipeline. We've worked with MongoDB to build all of that into a single, open platform, so teams can go from prototype to production without rearchitecting their data layer.
The teams we work with have a common pattern. They build an a...
The integration of AI agents with MongoDB Atlas offers a streamlined and open platform for teams to transition from prototypes to production without rearchitecting their data layer. However, the success of this collaboration hinges on its ability to address common challenges in production environments such as durable state, retrieval over real enterprise data, querying structured databases, and end-to-end tracing when something goes wrong. By reducing the need for additional infrastructure and o...