Couchbase, the Operational Data Platform for AI, has announced major expansion of its AI Data Plane with new capabilities including native Amazon Bedrock integration with semantic caching, managed Agent Memory and managed MCP server on AWS, in addition to vector search within Couchbase Operational Insights. Together innovations give enterprise teams single governed platform to replace fragmented data services that slow agent deployments, reducing both infrastructure burden and cost of running production AI at scale.
Enterprise teams deploying production AI agents finding general-purpose databases and stitched-together data services cannot keep pace with agentic workloads. Need converged data layer serving both agents and applications with live trusted data at scale in cloud, private data center, and at edge even offline.
Agents generate 450% more data-layer traffic per task than humans performing same work, and 83% organizations report needing infrastructure upgrades before can run production-grade agentic AI. Machine traffic surpassed human traffic in June 2026 with 57.5% of web requests now automated rather than human-initiated eighteen months ahead of forecasts.
Couchbase's elastically scalable distributed architecture serves millions concurrent low-latency operations without bottlenecks. Memory-first design and shared-nothing topology mean parallel agent requests resolve at sub-millisecond latency. Unifies key-value, SQL, full-text search, vector search, and real-time columnar analytics on single JSON dataset so agents get operational and historical context in one call. Couchbase Mobile lets enterprises run AI-capable applications on devices and at edge with full functionality even when connectivity drops.
"Couchbase has been a key component in achieving high availability in Mavenir's voice solutions for years," said Brandon Larson, SVP & General Manager, Cloud, AI & IMS Business Strategy. "Now we're creating new AI voice services that require getting reliable context fast and Mavenir is building that context layer with Couchbase because of their proven performance in production."
Native Amazon Bedrock Integration with Semantic Caching expanded Model Service with native Bedrock integration giving serverless pay-per-token access to hundreds foundation models along with vectorization over private networking. Inference and embedding generation now run alongside data without separate GPU management. Opens direct path to semantic caching where semantically similar queries served from cache instead of re-invoking model.
Managed Agent Memory gives agents durable low-latency memory layer persisting profiles conversation history vectorized facts across sessions so agents pick up where left off. Managed MCP server gives agents and tools governed open-standard path to Couchbase data.
"Customers building production AI agents at scale need a converged data layer, but most are still running three or four separate systems for memory, vectors, operational data, and analytics, each carrying its own sync logic, security model, and failure mode," said Barry Morris, Chief Product and Strategy Officer at Couchbase. "What we're shipping now collapses that stack. The new capabilities all sit on one governed platform that runs identically in the public cloud, a private data center, or at the edge. This is helping Couchbase customers reduce costs, accelerate productivity, and realize faster ROI on AI initiatives."
