Demo

Learn how to connect multiple RavenDB AI Agents into a multi-agent system, where specialized sub-agents handle focused tasks while a coordinator routes work between them.

Learn how to attach binary files such as PDFs and images to RavenDB AI Agent conversations, reducing token usage while keeping files accessible across the conversation lifecycle.

Learn how to implement spatial search in RavenDB with Python. Covers radius queries, custom polygon shapes, WKT syntax, and reverse point-in-polygon lookup using the Flat Finder demo.

External

Read about Building a Beer Vending Machine with RavenDB Embedded on the RavenDB.net news section

External

Read about GenAI: How We Make You Work Less on the RavenDB.net news section

Build a semantic search API with RavenDB, Python, and FastAPI. Learn manual and automatic embedding generation with OpenAI, and run vector similarity search in under 50 lines of application code.

Learn how to use RavenDB's GenAI feature to automatically summarize, prioritize, and enrich documents. Step-by-step walkthrough with code examples and screenshots.

Add AI-driven vector search to a Next.js app using RavenDB's embeddings generation AI Task and a single vector.search RQL query, almost like using a regular search API.

See how RavenDB Data Subscriptions let you offload invoice processing to a background worker in C#, with PDF generation and attachment storage included.