> For the complete documentation index, see [llms.txt](https://docs.vectra.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.vectra.ai/readme.md).

# Welcome

This is the home page for docs.vectra.ai.

## Introduction

Welcome to the home of documentation for Vectra AI.

Our documentation lives on this site, providing easy access to detailed guides and resources to help you deploy, configure, integrate, and operate your Vectra AI deployment. Meanwhile, our Knowledge Base articles, support cases, and product downloads are hosted on our dedicated support portal at [support.vectra.ai](https://support.vectra.ai). This division ensures that users can quickly find in-depth documentation here while accessing KBs and technical assistance through our support portal.

The [support portal](https://support.vectra.ai/) has a unified search feature available. This allows users to easily locate answers by searching content on both this documentation site and on the support portal. This unified search feature aims to streamline the search experience, ensuring users can efficiently find information from both comprehensive docs and targeted KB articles without navigating multiple resources. This documentation site will only search the content housed in it.

For Vectra Fusion customers, the current documentation can be found at [docs.fusion.vectra.ai](https://docs.fusion.vectra.ai/). As part of our integration roadmap, we will be working towards merging these resources with our comprehensive documentation here. This transition aims to provide a unified and streamlined experience, ensuring all users have access to consistent and consolidated information in one location. Keep an eye out for updates as we progress with this integration later this year.

## Docs vs KBs

**Docs (Documentation)** refers to comprehensive guides, user manuals, and detailed resources designed to help users understand and make the most of a product. They are typically structured, well-organized, and provides step-by-step instructions, ensuring that users can achieve specific tasks or solve complex issues independently.

**KBs (Knowledge Base articles)**, on the other hand, are focused on providing quick solutions to specific questions or common issues users may encounter. KBs are generally shorter than documentation, addressing particular problems, and often include advice for specific situations, troubleshooting steps, FAQs, etc.

In summary, while documentation offers in-depth educational content, KB articles provide immediate, targeted solutions, making it easier for users to find answers quickly during specific situations. Vectra support personnel may point you to docs or KBs depending on the issue you face.

## Future Plans

Vectra plans to migrate live api documentation to this site in a future update. For now, continue to use [apidocs.vectra.ai](https://apidocs.vectra.ai/) for live documentation of v3 and higher versions of Vectra APIs. PDF documentation for Vectra's v2.x APIs, can be found [here](/configuration/access/api-qux.md) on this site.

Please check the [Release Notes](https://docs.vectra.ai/release-notes/) section for details on both Vectra Product updates and major updates to the documentation site.

## Have Feedback or Need a .pdf

**To provide article feedback:**

<div data-with-frame="true"><figure><img src="https://4227135129-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FHJ1ltuWFvsArFWtevnRn%2Fuploads%2FnTAdoaCFVEBuOv7IzMPK%2Fimage.png?alt=media&amp;token=f72f83aa-2d54-4eb6-886c-d3bedbf0bf68" alt="" width="257"><figcaption></figcaption></figure></div>

All articles have a **Was this helpful?** area in the table of contents for each article on the right hand side. After clicking on a level of emotion to associate with your feedback, you can enter text to accompany your feedback if desired. Be as verbose as necessary. Vectra will be reviewing this feedback and trying to address it.

If you feel that you need a more official response, feel free to open a ticket on the [support portal](https://support.vectra.ai/).

**To create .pdf from native articles for reading offline:**

All article pages have an AI Assistant button near the top right of the page.

<div data-with-frame="true"><figure><img src="https://4227135129-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FHJ1ltuWFvsArFWtevnRn%2Fuploads%2Fy6csovu9pRDUWhTjBNjR%2Fimage.png?alt=media&amp;token=bd93ac35-1e73-41ee-98b9-af0752df50ad" alt="" width="563"><figcaption></figcaption></figure></div>

Simply select **Export as PDF** to export the page and any sub-pages under it as a .pdf.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.vectra.ai/readme.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.