AI Integration

Ship AI-powered features faster with RavenDB’s native tools.

Native AI features that create intelligent applications

RavenDB is equipped with a set of powerful native AI features that can be used independently or in conjunction with each other, allowing you to easily integrate advanced AI capabilities into your applications. These features include AI agents, GenAI tasks, Embeddings generation, and Vector search.

Use cases

RavenDB AI features help you ship any AI-related scenario quickly, including:

Conversational intelligence - Natural-language chatbots, assistants, and interactive workflows.
Automated content enrichment - Summarization, translation, classification, and document enhancement.
Semantic representation - Creating vector representations for text, images, and other data types.
Similarity-based discovery - Finding related items, aggregation, and context-aware retrieval.
Personalization & recommendations - Tailoring suggestions, feeds, and user experiences.
Content moderation & compliance - Automatically handling sensitive, inappropriate, or non-compliant content.
Knowledge management & Q&A - Asking questions over policies, wikis, and documents; retrieving answers and citations.

Learn more: In-depth AI features articles

External

RavenDB GenAI deep dive

A deep-dive with hands-on examples and implementation details, by Oren Eini

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External

Practical look at AI agents with RavenDB

A step-by-step tutorial for building AI agents with RavenDB, by Gracjan Sadowicz

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AI agents

AI agents are conversational proxy components that reside on the server and autonomously handle client requests using an AI model. Instead of spending your time on integrating AI capabilities into your application, you can rapidly configure AI agents using Studio or the client API. Agents can securely read from the database and request the client for actions on behalf of the AI model, infusing intelligence into the workflow. Whether you need chatbots, automated reporting, or intelligent data processing, you get immediate production-ready AI features without the integration overhead.

AI agents start page

Continue to the AI agents Start page.

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Technical documentation

Learn how to create, deploy, manage conversations, and get results with AI agents.

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GenAI tasks

GenAI tasks are configurable ongoing operations that process your documents systematically in the background using an AI model. Instead of building custom AI integration pipelines yourself, you can easily create tasks that weave AI capabilities into your data flow. They can enrich documents with AI-generated content, validate and categorize data, translate documents, or execute countless other automated workflows that leverage AI capabilities.

GenAI tasks start page

Continue to the GenAI tasks Start page.

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Technical documentation

Learn to create GenAI tasks that process your data and enable intelligent workflows automation.

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Embeddings generation

Embeddings generation tasks transform your content into semantic vectors that enable intelligent similarity-based searches. Instead of building complex search infrastructure, you can utilize native tasks that seamlessly embed vector capabilities into your data, enabling intelligent search by meaning and context.

Embeddings generation Start page

Continue to the embeddings generation Start page.

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Technical documentation

Learn to generate embeddings and enable intelligent searches.

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Vector search

Vector search enables intelligent similarity-based discovery using embeddings rather than exact matching. Instead of developing custom similarity algorithms yourself, you can employ native vector operations for diverse applications. Whether you need to categorize content, find similar items, or automate recommendations, vector search delivers intelligent matching capabilities that understand meaning and context.