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Added start pages for the AI integration branch and the embeddings and vector search sections #2167

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AI start pages (new start pages for the AI integration branch and the…
reebhub Nov 2, 2025
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AI start pages - added links
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39 changes: 22 additions & 17 deletions docs/ai-integration/ai-agents/ai-agents_overview.mdx
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Expand Up @@ -26,33 +26,17 @@ import LanguageContent from "@site/src/components/LanguageContent";
* Delegating the communication with the LLM to an AI agent can significantly reduce client code complexity and development overhead.

* In this article:
* [Common use cases](../../ai-integration/ai-agents/ai-agents_overview#common-use-cases)
* [Defining and running AI agents](../../ai-integration/ai-agents/ai-agents_overview#defining-and-running-an-ai-agent)
* [The main stages in defining an AI agent](../../ai-integration/ai-agents/ai-agents_overview#the-main-stages-in-defining-an-ai-agent)
* [What is a conversation](../../ai-integration/ai-agents/ai-agents_overview#what-is-a-conversation)
* [Initiating a conversation](../../ai-integration/ai-agents/ai-agents_overview#initiating-a-conversation)
* [AI agent usage flowchart](../../ai-integration/ai-agents/ai-agents_overview#ai-agent-usage-flowchart)
* [Streaming LLM responses](../../ai-integration/ai-agents/ai-agents_overview#streaming-llm-responses)
* [Reducing throughput and expediting LLM response](../../ai-integration/ai-agents/ai-agents_overview#reducing-throughput-and-expediting-llm-response)
* [Common use cases](../../ai-integration/ai-agents/ai-agents_overview#common-use-cases)

</Admonition>

## Common use cases

AI agents are designed to easily integrate AI capabilities into applications and workflows. They can interact with users, intelligently retrieve and process data from proprietary databases, and apply actions based on roles they are requested to take and the data they have access to. Some of the tasks and applications they can be tailored to perform include:

<a id="customer-support-chatbot-agents"/> **Customer support chatbot agents** can answer customer queries based on information stored in databases and internal knowledge bases, provide troubleshooting steps, and guide users through processes in real time.

<a id="data-analysis-and-reporting-agents"/> **Data analysis and reporting agents** can analyze large datasets to extract relevant data and present it in a user-friendly format, escalate customer issues and application output, create reports and highlight points of interest, and help businesses make informed decisions.

<a id="automated-content-generation-agents"/> **Automated content generation agents** can generate summaries, add automated comments to articles and application-generated content, reference readers to related material, and create marketing content based on user input and stored information.

<a id="workflow-automation-agents"/> **Workflow automation agents** can automate repetitive tasks such as email sorting, spam filtering, form filling, or file organization.

<a id="intelligent-recommendation-agents"/> **Intelligent recommendation agents** can provide personalized recommendations based on user preferences and available data, e.g. a _library assistant_ suggesting books and other resources, an _HR office assistant_ recommending rewards for employees based on their performance and available facilities near their residence, or an _e-commerce assistant_ recommending products.

<hr />

## Defining and running an AI agent

AI agents can be created by RavenDB clients (providing they have database administration permissions).
Expand Down Expand Up @@ -265,3 +249,24 @@ When creating query tools -
You can limit the number of times that the LLM is allowed to trigger database queries in response to a single user prompt.

[Setting iterations limit using the API](../../ai-integration/ai-agents/creating-ai-agents/creating-ai-agents_api#set-maximum-number-of-iterations)

<hr />

## Common use cases

AI agents are designed to easily integrate AI capabilities into applications and workflows. They can interact with users, intelligently retrieve and process data from proprietary databases, and apply actions based on roles they are requested to take and the data they have access to. Some of the tasks and applications they can be tailored to perform include -

#### <u>Customer support chatbot agents</u>
Agents can answer customer queries based on information stored in databases and internal knowledge bases, provide troubleshooting steps, and guide users through processes in real time.

#### <u>Data analysis and reporting agents</u>
Agents can analyze large datasets to extract relevant data and present it in a user-friendly format, escalate customer issues and application output, create reports and highlight points of interest, and help businesses make informed decisions.

#### <u>Content generation agents</u>
Agents can generate summaries, add automated comments to articles and application-generated content, reference readers to related material, and create marketing content based on user input and stored information.

#### <u>Workflow automation agents</u>
Agents can automate repetitive tasks like email sorting, spam filtering, form filling, or file organization.

#### <u>Intelligent recommendation agents</u>
Agents can provide personalized recommendations based on user preferences and available data, e.g. a _library assistant_ suggesting books and other resources, an _HR office assistant_ recommending rewards for employees based on their performance and available facilities near their residence, or an _e-commerce assistant_ recommending products.
54 changes: 27 additions & 27 deletions docs/ai-integration/ai-agents/ai-agents_start.mdx
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Expand Up @@ -5,54 +5,54 @@ sidebar_label: Start
sidebar_position: 0
---

import Admonition from '@theme/Admonition';

import CardWithImage from "@site/src/components/Common/CardWithImage";
import CardWithImageHorizontal from "@site/src/components/Common/CardWithImageHorizontal";
import ColGrid from "@site/src/components/ColGrid";
import aiAgentsStartOvImage from "./assets/ai-agents_start_ovImage.png";
import aiAgentsStartApiImage from "./assets/ai-agents_start_apiImage.png";
import aiAgentsStartStudioImage from "./assets/ai-agents_start_studioImage.png";

# 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](../../ai-integration/ai-agents/ai-agents_overview#customer-support-chatbot-agents)
- [Data analysis and reporting agents](../../ai-integration/ai-agents/ai-agents_overview#data-analysis-and-reporting-agents)
- [Automated content generation agents](../../ai-integration/ai-agents/ai-agents_overview#automated-content-generation-agents)
- [Workflow automation agents](../../ai-integration/ai-agents/ai-agents_overview#workflow-automation-agents)
- [Intelligent recommendation agents](../../ai-integration/ai-agents/ai-agents_overview#intelligent-recommendation-agents)
# AI Agents
### Create conversational AI proxies for your applications.

AI agents are server-side components that act as secure proxies between RavenDB clients and AI models. They can be easily customized to handle specific client needs, tasks or workflows, such as answering questions, performing data analysis, or automating processes.
- Using AI agents frees developers from the need to manage the communication with the AI model in their code, and enables rapid integration of AI capabilities into their applications.
- An agent receives requests from clients and maintains continuous conversations with AI models to fulfill them. During the conversation, the agent can enable the model to securely query a RavenDB database (e.g., fetch recent orders or run vector searches on products) and request the client to perform actions (like sending emails or creating new orders).
- You can use AI agents to quickly create an intelligent, actionable, conversational interface for your applications, in a way that abstracts much of the complexity of AI integration.
- [See common AI agents use cases](../../ai-integration/ai-agents/ai-agents_start#use-cases)

## Technical documentation
Use the technical documentation to learn how to create and manage AI agents, configure secure database access, enable agents to trigger client actions, and more.

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](../../ai-integration/ai-agents/ai-agents_overview) page as a good starting point.
<ColGrid colCount={3}>
<CardWithImage title="AI Agents Overview" description="Basic concepts of RavenDB's native AI agents" url="../../ai-integration/ai-agents/ai-agents_overview" imgSrc={aiAgentsStartOvImage} imgAlt="imgAlt" ctaLabel="Read" />
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@mateuszbartosik mateuszbartosik Nov 12, 2025

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Use descriptive imgAlt

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@reebhub reebhub Nov 13, 2025

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done

<CardWithImage title="Create agents via the API" description="Define and run AI agents via the Client API" url="../../ai-integration/ai-agents/creating-ai-agents/creating-ai-agents_api" imgSrc={aiAgentsStartApiImage} imgAlt="imgAlt" ctaLabel="Read" />
<CardWithImage title="Create agents via Studio" description="Easily create and test AI agents using Studio" url="../../ai-integration/ai-agents/creating-ai-agents/creating-ai-agents_studio" imgSrc={aiAgentsStartStudioImage} imgAlt="imgAlt" ctaLabel="Read" />
</ColGrid>

## In-depth articles
Once you get acquainted with AI agents, expand your expertise with a comprehensive guide that includes some practical insights.

<ColGrid colCount={3}>
<CardWithImage title="AI Agents - Overview" description="The starting point for the AI agents documentation: an overview of the feature" url="../../ai-integration/ai-agents/ai-agents_overview" imgSrc={aiAgentsStartOvImage} imgAlt="imgAlt" ctaLabel="Read" />
<CardWithImage title="Creating an agent using the API" description="Defining an agent configuration, Running a continuous conversation with the LLM, and Getting results via the Client API" url="../../ai-integration/ai-agents/creating-ai-agents/creating-ai-agents_api" imgSrc={aiAgentsStartApiImage} imgAlt="imgAlt" ctaLabel="Read" />
<CardWithImage title="Easily creating and testing an AI agent using Studio" url="../../ai-integration/ai-agents/creating-ai-agents/creating-ai-agents_studio" imgSrc={aiAgentsStartStudioImage} imgAlt="imgAlt" ctaLabel="Read" />
<CardWithImage title="Practical Look at AI Agents with RavenDB" description="A step-by-step tutorial for building AI agents with RavenDB, by Gracjan Sadowicz" imgSrc="" url="https://ravendb.net/articles/practical-look-at-ai-agents-with-ravendb" imgAlt="imgAlt" ctaLabel="Read" />
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Use imgIcon="ai-agents"; remove imgSrc and imgAlt

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@reebhub reebhub Nov 13, 2025

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done

</ColGrid>

## Videos

Watch our webinars to see AI agents in action and learn practical implementation techniques.

<ColGrid colCount={2}>
<ColGrid colCount={1}>
<CardWithImageHorizontal title="How to run AI agents natively in your database" description="Webinar with Oren Eini" url="https://www.youtube.com/watch?v=A17GSLGN-cQ" imgSrc="https://media.licdn.com/dms/image/v2/D4D10AQG81cXtiYRc2w/image-shrink_800/B4DZZYYLcTHwAk-/0/1745239456036?e=2147483647&v=beta&t=yQVz6ji4wD4reOTXtlPpERK0fdpr1f2VoG_SEV9x3lc" imgAlt="imgAlt" ctaLabel="Watch" />
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These webinars have the same thumbnail image.

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done

<CardWithImageHorizontal title="How to create powerful and secure AI agents with RavenDB" description="Webinar with Oren Eini" url="https://www.youtube.com/watch?v=jzUxL9P17G4" imgSrc="https://media.licdn.com/dms/image/v2/D4D10AQG81cXtiYRc2w/image-shrink_800/B4DZZYYLcTHwAk-/0/1745239456036?e=2147483647&v=beta&t=yQVz6ji4wD4reOTXtlPpERK0fdpr1f2VoG_SEV9x3lc" imgAlt="imgAlt" ctaLabel="Watch" />
</ColGrid>

## In-depth articles
## 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 -

Once you get acquainted with AI agents, expand your expertise with a comprehensive guide that includes some practical insights.
- [Customer support chatbot agents](../../ai-integration/ai-agents/ai-agents_overview#customer-support-chatbot-agents)
- [Data analysis and reporting agents](../../ai-integration/ai-agents/ai-agents_overview#data-analysis-and-reporting-agents)
- [Content generation agents](../../ai-integration/ai-agents/ai-agents_overview#content-generation-agents)
- [Workflow automation agents](../../ai-integration/ai-agents/ai-agents_overview#workflow-automation-agents)
- [Intelligent recommendation agents](../../ai-integration/ai-agents/ai-agents_overview#intelligent-recommendation-agents)

<ColGrid colCount={3}>
<CardWithImage title="Practical Look at AI Agents with RavenDB" description="Article by Gracjan Sadowicz" imgSrc="" url="https://ravendb.net/articles/practical-look-at-ai-agents-with-ravendb" imgAlt="imgAlt" ctaLabel="Read" />
</ColGrid>
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