Requirements
To use the Omni Agent, you’ll need:- Restricted Querier, Querier, Modeler, or Connection Admin permissions
- To verify that the following settings in AI Hub > General > Features are enabled. These settings are enabled by default, but Organization Admins can modify them as needed.
- Omni Agent - Required to use the Omni Agent
- Omni Agent > Chat - Required to access the chat interface
- Omni Agent > Chat > Chat in navigation - Required to show the standalone chat in the main sidebar
Accessing the Omni Agent
To access the Omni Agent, you can:- Click the New button in the sidebar, then select Chat.
- Click Omni Agent in Omni’s main sidebar.
The Omni Agent sidebar item may display differently or not at all if your organization uses a custom sidebar. Your organization's AI branding settings can also change the label of this item in the sidebar.
Capabilities
The Omni Agent can:- Answer natural-language questions about your data
- Search existing dashboards for tiles and visualizations that already answer your question before generating a new query
- Generate queries based on your prompts, routed through topics or any view in your model
- Create visualizations, including KPI tiles, directly from your prompts
- Create dashboards based on the queries and visualizations in the session
- Create input columns to annotate query results inline. Refer to Input columns to learn more.
- Create, edit, find, and delete routines
- Accept files and images as context:
- Upload files including text and Markdown files to provide additional context alongside your queries
- Attach images by pasting from your clipboard to provide visual context for your questions
- Save information about you to memory to provide more personalized responses
- Search the Omni docs to answer questions about how to use Omni
- Search the web for real-time information, when enabled in AI settings
Getting help
If you’re stuck and can’t remember how to do something in Omni, ask the Omni Agent. Questions like “How do I do [thing]?” will prompt the agent to search the official Omni docs and provide you with an answer, all without leaving your Omni workflow. You can also directly tell the agent to search the docs when researching the answer to your question.Working in an embedded context? If you have the Hide Omni watermark setting enabled to provide a fully white-labeled experience, the AI doc search feature will respect it. Omni doc links will not be returned in chat, even if explicitly requested.
Tuning responses
You can shape how the Omni Agent responds by scoping which data it draws from, controlling the context it can access, and choosing which underlying AI model handles your prompts.Scoping responses
The Omni Agent uses pickers to scope responses to specific connections, models, and topics. Click the button at the bottom of the chat box to open the pickers:
Connection, model, and topic picker in Omni's chat interface
- Connections - Lists the connections you have access to. Only displays if more than one connection is available. This setting can’t be changed if you’re using the chat in a workbook or dashboard.
-
Models - Lists the available models in the selected connection. Only displays if:
- The connection has more than one model, and
-
At least one topic in the model is accessible. This could mean that the model’s
ai_chat_topicsis unset, making all topics accessible, or that it specifies at least one topic:Organization Admins can configure a default model in AI Hub > Setup > Features to set which model the Omni Agent opens with by default.
-
Topics - Lists the available topics in the model. Only displays if at least two topics in the model are accessible. This could mean that the model’s
ai_chat_topicsis unset, or that it specifies at least two topics:Organization Admins can configure a default topic in AI Hub > Setup > Features to set which topic the Omni Agent opens with by default.
Scoping topics
If a prompt is entered and a topic isn’t selected - meaning that Auto-select a topic is selected in the topic picker - the AI will attempt to select the most relevant topic. To scope the AI’s response to a specific dataset, use the pickers to select a specific topic or composite topic. The AI will remain “locked” to the selected topic until the selection is changed. If an Organization Admin has configured a default topic along with a default connection and model, a new chat starts “locked” to that topic the same way - the AI asks for confirmation before switching away from it. Additionally, the picker menus won’t display when a model only has one AI-accessible topic. If a connection has one model with a single AI-accessible topic - determined by the value of the model’sai_chat_topics parameter - the AI will be scoped only to that topic and the pickers will not display.
Managing AI integrations
This feature is not supported in embedded Omni instances.
- Connect - If you haven’t connected your account yet, click Connect to launch the OAuth flow. This is the same authentication flow available from your user account settings.
- On/Off toggle - If you’ve already connected your account, the integration displays an on/off toggle. Turning the toggle off temporarily withholds that integration’s tools from the Omni Agent for your session without disconnecting your account. You can turn the integration back on at any time.
Saving information to memory
The Omni Agent > AI memory AI setting must be enabled to use this feature. Additionally, user memory is not supported for embedded instances.
- Omni Agent
- Omni UI
Selecting an LLM
The Omni Agent provides an LLM picker that allows you to choose which LLM answers your prompt. Only LLMs that an Organization Admin approved in LLM settings display in the picker. New chats start by using your organization’s default LLM. To select a different LLM, click the LLM picker next to the icon and choose an LLM from the dropdown menu. Your selection applies to prompts sent after you make it and persists until you select a different LLM. If you close the chat and open it again, the chat still uses the LLM you selected. To return the chat to your organization’s default LLM, choose Default AI in the picker. A new chat starts on your organization’s default LLM.The LLM picker won’t display if your organization only has one approved LLM or you’re in an embedded Omni session.
Searching existing dashboards
Before generating new queries, the Omni Agent can search for existing dashboards that might already answer your question. When you ask a question, the AI analyzes your prompt and searches through:- Dashboard names - Searches the content index for dashboards with relevant titles
- Tile and chart names - Searches for specific visualizations that match your question
1
Evaluates tiles
Uses semantic matching to identify which specific tile or chart from a dashboard best matches your question
2
Shows live previews
Executes the underlying query and displays the actual chart or table visualization inline in the chat
3
Highlights direct answers
If a tile directly answers your question, it displays in a highlighted card with an AI-generated explanation of why it’s relevant
Creating queries and dashboards
When the Omni Agent answers a question, it generates a live query you can inspect, refresh, or roll up into a dashboard alongside other charts from the session.Viewing query field details
When the Omni Agent generates a query, you can view details about the fields used in the results. This helps you understand what data the AI selected and how each field is defined. To view field details, click the icon near the top-right corner of the query results, next to the icon. A panel displays information for each field in the query, including:- Field name - The field’s label and identifier in the model
- Definition - The SQL or calculation that defines the field
- Description - Additional context about the field, if defined in the model

Refreshing query results
When you revisit a previous chat session, query results may be stale. To update the results with the latest data, click the icon floating above the chat box:
Creating dashboards
The Omni Agent can build dashboards. There are a few ways to get started:-
Ask the agent directly to build a dashboard — describe the dashboard you want in the chat and the agent plans the layout, generates queries, and publishes a complete dashboard:
“Create a dashboard showing sales performance by region with monthly trends and a top customers table” After the dashboard is created, you can ask the agent to iterate on it in the same session — rearranging tiles, editing charts, or adding new ones.
The dashboard saves to your My documents folder if your organization’s Allow personal content setting is enabled for you. If the setting isn’t enabled, the agent saves the dashboard to your organization’s shared Hub or your embed entity’s shared folder (embed users only), as long as you have permission to save there. If none of these destinations is available, the agent reports that it can’t save the dashboard and names who can grant you access. - From an existing chat — you’ve been exploring data and created a few visualizations in a chat session, ask the agent to pull them into a dashboard
- Upload an image — drop in an image of a dashboard you’d like to replicate. The agent parses what it sees and uses it as a starting point
create_dashboard_from_chat tool to a model’s ai_settings.disabled_tools. This setting is per-model, not organization-wide - you will need to set it on every model to disable dashboard creation from chat entirely.
Working with routines
The Omni Agent can create, edit, find and open your existing routines from chat, and delete a routine when it’s open in the split view. See AI Routines for more information.Adding files as context
The Omni Agent > File uploads AI setting must be enabled to upload files and attach images.
Uploading files
You can upload text (.txt), Markdown (.md), LookML (.lkml), XML (.xml), HTML (.html, .htm), CSV (.csv), and images to the Omni Agent to provide additional context for your questions. This is useful when you need to reference additional information alongside your data queries.
CSV files can be up to 50 MB. If a CSV is too large for the Omni Agent to read in full, the file stays in your browser and only its header row (column names) is sent to the agent. When this happens, the agent can’t answer questions about the file’s data, and will suggest uploading the CSV as a topic so you can query it.
Uploads can use up to 250,000 tokens total on an Omni-managed, 1M-context-window Claude or GPT model, or 50,000 tokens on other LLMs. This allowance is tied to the
conversation_prune_length parameter.- Click the icon at the bottom of the chat box
- Select Attach file
- Select a file from your computer
- The file appears as a file chip in the chat box, indicating it’s ready to be sent with your message
Attaching images
You can paste images directly from your clipboard into the chat to provide visual context alongside your questions. This works with screenshots, images copied from web pages, or any image data on your clipboard. To attach an image:- Copy an image to your clipboard (for example, take a screenshot or copy an image from a web page)
- Click into the chat box
- Paste the image using your system’s paste command (
Cmd+Von Mac,Ctrl+Von Windows/Linux)
Managing and sharing chat sessions
Each conversation with the Omni Agent is saved as a chat session you can revisit and share with other users in your organization.Navigating prompt history
You can quickly recall previous prompts using keyboard shortcuts, similar to a command-line interface:- Press the Up arrow key to cycle backward through your previous prompts
- Press the Down arrow key to cycle forward through your prompt history
Arrow key navigation only works when your cursor is at the beginning of the input field or when the field is empty. This preserves normal cursor movement when editing text.
Managing long conversations
As your conversation with the Omni Agent grows, it consumes more of the available context window. Omni automatically prunes older messages from the conversation history in the background to stay within that window, governed by theconversation_prune_length parameter.
This happens automatically and requires no configuration or action from you.
Sharing chat sessions
You can share a chat session by copying the URL from your browser’s address bar and sending it to another user. Query results stored in the chat history are cached from when the creator ran them. The viewer of the shared chat will see those same cached results. Therefore, Omni requires that the viewer of the shared chat have Querier, Modeler, or Connection Admin permissions, as well as the same connection environment, to view the session. Users with Restricted Querier permissions or lower will not be able to access shared chat sessions. The following rules determine who can see a chat:- The owner of the chat can always view the chat.
- Any user with the Querier role or above on all relevant models can view the chat. Because Queriers can already write SQL queries directly in Omni, this doesn’t expose any data they couldn’t otherwise access.
- Viewers and Restricted Queriers are blocked from viewing, preventing access to data they are not authorized to see.
Customizing and embedding the Omni Agent
Organization Admins can tailor the agent’s appearance to match their brand and surface it inside external applications.Applying branding
Organization Admins can customize the appearance of the AI chat interface, including the agent’s name, icon, and greeting messages. Refer to the AI branding settings for more information.Embedding the agent
The Omni Agent can also be embedded into external applications. Refer to the embedding the Omni Agent guide for setup instructions.Next steps
- Optimize your models for AI to improve the quality of AI-generated responses
- Configure topics to organize and scope the data the Omni Agent can access
- Customize the Omni Agent appearance with your own branding

