AI Agents: Start
AI agents are built to easily integrate AI capabilities into RavenDB clients.
An AI agent serves as a client's proxy to an AI model; the agent can not only maintain a continuous conversation with the model but also enable it to securely query a RavenDB database and request the client to perform actions.
Using AI agents frees developers from the need to manage an AI model in their code, enhances the model by giving it access to a credible and relevant data source, and opens the door to numerous operational scenarios.
Use cases
Creating an AI agent and assigning it a role can be done in minutes using Studio or the API, making it easy to address a wide variety of use cases like -
- Customer support chatbot agents
- Data analysis and reporting agents
- Automated content generation agents
- Workflow automation agents
- Intelligent recommendation agents
Technical documentation
Our technical documentation explains in detail what AI agents are and how to define and use them.
If you're new to AI agents, we recommend the overview page as a good starting point.
AI Agents - Overview
The starting point for the AI agents documentation: an overview of the feature
Read nowCreating an agent using the API
Defining an agent configuration, Running a continuous conversation with the LLM, and Getting results via the Client API
Read nowLives & videos
Take a look at our webinars and video content to see AI agents in action, and learn how to create and use them.
ExternalHow to run AI agents natively in your database (webinar recording)
Live webinar with RavenDB's CEO, Oren Eini
Watch nowExternalIn-depth articles
Once you get to know AI agents, find more about them here: