Join us for an engaging session as we delve into the versatile vector database capabilities of Azure Cosmos DB for MongoDB vCore. Discover the seamless integration of your operational and transactional data with native vector indexing and search functionalities, specifically tailored for AI applications. Learn how to swiftly build RAG solutions by seamlessly connecting with Azure AI Studio to create chatbots using your own data. Explore the power of Azure Cosmos DB's Copilot in simplifying complex query writing, enhancing accuracy, and improving performance. Additionally, we'll showcase our seamless integrations with Semantic Kernel, Langchain, and LlamaIndex. Gain valuable insights into KPMG's success story, where Azure Cosmos DB played a pivotal role in the creation of a generative AI assistant for business operations.

Learning Objectives

• Understand the architecture and features of Cosmos DB for MongoDB vCore

• Learn how to set up and use Cosmos DB for MongoDB vCore

• Explore use cases relevant to startups

• Participate in a live Q&A with Microsoft experts

This session is ideal for students/startups who are:

• Looking to understand the benefits of using Cosmos DB for MongoDB vCore

• Interested in learning how to implement and use Cosmos DB for MongoDB vCore

• Seeking to network with like-minded individuals and Microsoft professionals


Azure Cosmos DB for Mongo vCore Free tier: Aka.ms/tryvcore
Chatbot (Wheelie) Demo: Aka.ms/MongovCoreAzureAIsample
AI-advertisement: Aka.ms/adgen
RAG Jupyter Notebook Aka.ms/RAGwithCosmosDB
Microsoft Copilot for Azure in Cosmos DB: Aka.ms/CopilotForAzureInAzureCDBBlog
Azure AI Advantage: Aka.ms/AzureAIAdvantageBlog

#azurecosmosdb #ai #mongodb