Showing category results for AI

AI applications built on Azure Cosmos DB depend on embeddings for grounded results. Keeping them in sync with your data is the hard part: it means building and operating a separate data pipeline to track changes, call an embedding model, and write the results back to Azure Cosmos DB. In practice, that pipeline also has to handle failures and retrie...

Today we are open-sourcing OmniVec, a platform for building and operating the embedding pipelines that keep the vector representation of your operational data in sync as it changes. You register data sources, embedding model(s), vector stores (destination), and OmniVec does the rest: initial backfill, change tracking, model invocation to geenrate, ...

Since we introduced the Azure Cosmos DB MCP Toolkit at Ignite 2025 in preview, the response has been clear: developers want a straightforward way to connect AI agents to their production databases. Customers asked for stability, broader embedding provider support, and a smoother path from experimentation to production. Today, we're announcing th...

Today we’re thrilled to announce the public preview of Semantic Reranker in Azure Cosmos DB for NoSQL,a new AI-powered capability that improves the relevancy of your search results with just a few lines of code. If you’ve ever run a vector, full-text, or hybrid search and wished the most relevant documents bubbled to the very top, this one’s for yo...

Today we’re thrilled to announce the public preview of two new toolkits for Azure Cosmos DB: the Agent Memory Toolkit and the Agentic Retrieval Toolkit. If you’re building AI agents and retrieval-augmented generation (RAG) apps, these toolkits are designed to take you from prototype to production faster, giving your agents durable memory and your R...

The Problem Every Developer Knows Too Well You're building a feature. You know exactly what data you need all orders from the last week over $500, grouped by region. The logic is clear in your head. But between you and that data sits a query language, a documentation tab (or three), and fifteen minutes of trial and error before you get the synta...

Back in January, we shipped the Azure Cosmos DB Agent kit in preview with 45 rules and a hypothesis: if we package Azure Cosmos DB expertise into a format that AI coding agents understand, developers will stop making the same expensive mistakes. That hypothesis held up. What surprised us was how much the rules themselves needed to evolve once we st...

Microsoft Build 2026 has officially started and we’re excited to announce new capabilities for Azure Cosmos DB! We’ve launched new features to help developers build AI-powered applications and agents more easily, improve application resilience, and accelerate developer productivity. These announcements span every stage of the development lifecyc...

 Today, we're thrilled to announce the public preview of Azure Cosmos DB Shell – a powerful, open-source command-line interface that revolutionizes how developers interact with their Azure Cosmos DB databases. With integrated Model Context Protocol (MCP) server support, native agentic capabilities, and bash-like syntax, Azure Cosmos DB Shell transf...

Build AI Agents and RAG Applications with the New LangChain + LangGraph Connector for Azure Cosmos DB Building AI agents and RAG applications today means stitching together half a dozen services, a vector database, a chat history store, a checkpointer for agent state, a semantic cache, a long-term memory layer. Each adds operational overhead, late...