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This guide is not applicable if your organization is using a custom model provider.
Omni’s AI features consume credits each time they process a request. You can control this usage at two levels: across your entire organization, or for individual users. In this guide, you’ll learn what credits are, what drives consumption, how to set limits at both levels, and how to monitor usage across your account.

Requirements

Organization Admin permissions are required to access Omni’s AI credit controls and monitoring tools.

What are credits?

Credits are the unit of measurement for AI usage. Every interaction with an AI feature in Omni — such as asking a question, generating a summary, asking AI to make data model changes, or using the MCP Server — consumes tokens from an LLM provider. Omni rolls those up into credits. Credit usage varies depending on several factors:
  • Task complexity — More complex questions, multi-step analysis, or larger datasets use more credits than basic lookups. Each message in a session carries prior context, so long-running sessions can compound.
  • Data model and context size — Omni sends context from the data model to the LLM to improve answer accuracy (field descriptions, ai_context, synonyms, etc.). Larger data models use more credits.
  • LLM model — More capable models (e.g., Sonnet-class) consume more credits per request than lighter models (e.g., Haiku-class). See AI model settings to configure tiers.

Organization-level credit controls

The Credits tab in AI Hub > General includes settings that allow you to limit AI credit consumption at the organization level. The settings can be used individually or combined.
Accounts and organizations: Your Omni account represents your company — for example, Blobs R Us. Each account contains one or more organizations (also called instances), the individual Omni deployments you sign in to, such as blobsrus-usa and blobsrus-eu. AI credits are pooled at the account level, but managed per organization.

Set a hard cap on AI usage

Disables AI features when the specified credit threshold is reached. Using AI beyond the included amount shown requires enabling overage billing.
Requests that are processing when the cap is met will complete, but subsequent requests will be blocked. This means that the hard cap limit may be slightly exceeded to account for in-process requests.

Enabling overage billing

Some accounts may have AI usage automatically capped at their included credit allotment. If your account is hard-capped, Organization Admins will see a Review & accept banner on the Credits tab to enable overage billing. To enable overage billing, check the authorization box and click Agree & enable overage billing. This removes the usage cap for all organizations sharing the same billing account, allowing AI usage to continue beyond the included allotment.

Downgrade to a less expensive model

Switches AI features to a less expensive model (Claude Haiku) when the specified credit threshold is reached, reducing credit consumption.

Defining credit usage thresholds

To create a tiered approach, enable both the hard cap and downgrade settings. Set Downgrade to a less expensive model at a lower threshold than Set a hard cap on AI usage. As consumption rises, AI features switch to a less expensive model first, then stop entirely once the hard cap is reached.
To set a hard cap or less expensive model:
  1. Navigate to AI Hub > General.
  2. Click the Credits tab.
  3. Toggle the setting to on.
  4. In the credits field, enter the number of credits where usage should be hard-capped or downgraded.
  5. Click Save.

User-level credit controls

By default, users in your organization don’t have credit limits. Overall usage will be capped based on any organization-level controls you have defined, but limits for individual users are only enforced if you enable user-level credit limits. User-level credit limits can be set two ways:

Per-user default limit

A default limit sets a credit limit for each individual user in your organization. When defined, the default applies to all users in the organization that don’t have an individual AI credit limit configured. Default credit limits work alongside organization-level downgrade and hard cap thresholds. For example, you can set a per-user default of 10,000 credits while also configuring an organization-level hard cap of 500,000 credits to control total organizational usage. To define the per-user default credit limit:
  1. Navigate to Settings > Attributes.
  2. Click the AI credit limit attribute at the top of the attributes list.
  3. Enter the number of credits in the Default value field to set the organization-wide per-user default, or leave it empty to allow unlimited credits by default. All other fields are read-only.
  4. Click Save.

Individual user credit limits

Setting credit limits for individual users allows you to control how many credits specific users can consume. For example, you might set a higher limit for power users who rely heavily on AI features, or a lower limit for users who primarily work with static content. User-level limits are set using omni_ai_credit_limit user attribute. When a user-level limit is not set, the user inherits the organization’s per-user default limit. See User settings for more information. To configure a credit limit for a user:
  1. Navigate to Settings > Users.
  2. Click the tab (e.g., Standard, Embed) of the type of user you want to modify.
  3. In the list of users, click the user you want to modify.
  4. Next to AI credit limit, click the Edit button.
  5. In the dialog that displays, configure the user’s credit limit:
    • To set a cap, enter a whole number (ex: 40) in the Credit limit field
    • To allow unrestricted usage, click the Unlimited toggle
    • To remove the user’s current settings, click Unset. The user will inherit the organization’s per-user default limit on save.
  6. Click Save.

Embed entity group credit controls

Embed entity group controls only apply when embedding Omni.
If you’re embedding Omni, you can also set limits for entity groups in addition to organization and user-level settings. This allows you to control AI usage on a per-entity basis when embedding Omni for multiple customers or tenants. See Managing AI credits for embed entity groups for more information.

Monitoring credit usage

There are a few ways to monitor AI credit usage in Omni:

Check usage at a glance

High-level AI credit information can be accessed in the AI Hub > General > Credits tab or through the API.
The Credits tab in AI Hub > General displays your total credit usage for the current month. The visualization behavior depends on whether your account has a single organization or multiple. Click the tabs below for more information.
For accounts with only one organization, the usage chart always appears and displays your current usage plotted against your included credit allotment and any thresholds you’ve configured. This gives you a quick way to see how close you are to downgrading or reaching your hard cap.
Usage visualization for an Omni account with a single organization

Usage visualization for accounts with a single organization

The chart includes:
  • Included — The credit allotment included with your plan
  • Downgrade and Cap — The thresholds you’ve set, if any
  • Credits used this month — The organization’s current usage, with color-coded bars that transition from green when you’re within limits to red as usage approaches the cap

Analyze usage in detail

The Credit Tracking dashboard helps you understand how credits are being used in greater detail. You can access it:
  • In the AI Hub — Select Credit tracking in the left navigation. Note that unlike the other AI Hub dashboards, this dashboard is not filterable by the shared model selector, since credit usage reflects activity across all models.
  • In Analytics — Click Analytics in the left navigation and select the Credit Tracking dashboard.
The dashboard displays credit consumption over time and can break down usage in various ways, such as by feature and user.

Optimizing credit usage

  • Adjust the LLM model tier. See AI model settings.
  • Trim unused fields, descriptions, or ai_context from the data model. Reducing context may lower per-call credit counts, but can increase the number of turns needed to get a good answer. The goal is optimizing efficiency overall.
  • If using Claude, use the ai_settings.conversation_prune_length parameter to control how aggressively conversation context is managed. When conversation context reaches the specified token threshold, older messages are automatically pruned from the conversation history to stay within limits.
See Tuning Omni AI for cost and quality for additional credit usage optimization tips.

Common questions

AI usage is calculated on a monthly basis and resets on the first of the month at 12AM UTC.
Omni’s AI is an agentic system. For a given prompt or request, it may fire off multiple tool calls to get the answer or complete the task.For example, asking “show me revenue by region” might involve the AI searching the data model for the right fields, building the query, creating a visualization, and summarizing results — each as a separate step. Each of these steps is logged individually in the tracking data, which is why a single user prompt can appear as several rows.
These are “tool calls” — intermediate steps where the AI determines which action to take next. They don’t have a user-facing prompt because they are part of the AI’s internal reasoning as it works through a request. See the question above for more context on why these occur.
Credit usage can vary between identical prompts due to differences in conversation context (earlier messages in the session) or the AI choosing a different path to arrive at the answer.
Omni caches AI summaries/sub-titles/descriptions so they will only recompute and use credits any time the data changes underneath (e.g., when a filter changes or it’s refreshed without cache).
This banner appears when your account has reached its included credit allotment and AI usage has been automatically capped. To continue using AI features beyond the included amount, an Organization Admin needs to review and accept the overage billing amendment. Once accepted, AI usage can continue and your organization will be billed at $1.00 per credit for usage beyond the included allotment.

Next steps