AI Credits Dashboards for Admins

Engineers use AI Credits when talking to the Assistant or using an agent to help them complete their work, and when training AI Physics models. Admins can now see exactly where their AI Credits are going. Two new admin pages show the workspace credit balance for each product, how it has been spent day by day, which users are spending it, and the details of every credit on the account — so you can spot a fast burn rate weeks before anyone gets blocked mid-task.

Highlights

  • A balance you can actually see: Total AI Credits, consumed to date, remaining, and percent consumed, in one card per product at the top of the dashboard
  • Day-by-day burn chart: See which days drove consumption, with a separate colored series per product, and switch months to compare a heavy week against a quiet one
  • Consumption by user: A ranked table of who used the most credits in the selected month, broken out by product, so you can tell the difference between broad team adoption and one large exploratory session
  • Three months of history: Prior-period totals sit next to the current month, giving you a trend instead of a snapshot
  • Credit-level detail: Every credit on the account with its product, issue date, original amount, consumed and remaining balance, and expiration date — plus a per-credit CSV export for your own reporting

What You Can Answer Now

The dashboards are built around common credit-related questions:

  • “How many AI Credits does this workspace have left, in each pool?”
  • “Are we on pace to run out before the license renews?”
  • “Who on my team is using the Assistant and agents the most?”
  • “Is AI Physics training or Assistant usage driving our burn?”
  • “Was last month heavier or lighter than this one?”
  • “When does this credit expire, and how much of it is left?”
  • “Can I get the raw consumption numbers into my own spreadsheet?”

Get Started

Open the Organization Administration Portal or your Workspace Administration Portal, then go to Dashboards → AI Credits Utilization. Use the month picker in the title bar to change the period. The Consumption by User table has an export link to pull the same data as a CSV.

For credit-level detail, go to Financials → AI Credits. Each row is one credit — a license allocation or a top-up — with its own CSV link for a per-credit consumption report.

Organization admins see credit data aggregated across all workspaces in the organization, with a Workspace column identifying where each user’s consumption came from. Workspace admins see their own workspace only. No setup is required — access follows your existing admin role.

For complete documentation, see the AI Credits documentation.

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The AI Credits Utilization dashboard: balance card, daily burn chart, consumption by user, and prior periods

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The AI Credits page under Financials, showing each credit with its remaining balance and expiration date

Good to Know

Numbers update on a daily cycle, not instantly. Consumption is rolled up several times a day, so a conversation you just finished with the Assistant may not appear in the charts or the CSV until the next rollup. The balance figure accounts for the current day’s usage; the per-user tables and consumption reports reflect completed rollups. If you are checking whether a specific interaction was tracked, look the following day.

Credits are shared across the workspace. Neither pool is divided per person — any user in the workspace draws from the same balance, which is why the Consumption by User table matters. Per-user caps are not part of this release.

Watch your email as well as the dashboard. Admins receive notifications at 50%, 80%, and 100% consumption. When a pool reaches zero, the features it covers stop for everyone in the workspace until credits are added, so treat the 80% notice as your cue to talk to your Rescale account team about a top-up.

The two pools burn differently. Agentic Engineering credits are consumed variably by the size of each Assistant or agent interaction — a quick question costs a fraction of what a long analysis over a large body of context does. AI Physics credits are consumed at fixed hourly rates for training, so its line on the burn chart tracks hours run rather than conversation length. Expect the two series to look differently.

Each pool is spent separately. Agentic Engineering and AI Physics credits are tracked independently and cannot be spent interchangeably — running out of one pool does not affect the other pool. The dashboard shows both cards side by side and the tables break consumption out by product.

Feedback

Questions about credit balances, top-ups, or anything that looks wrong on either page: contact your Rescale account team or support.

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