How to monitor your team’s credit consumption and Parabola activity — and how to use that data to make decisions.
When your management team asks “how are we using Parabola?” or “are we getting value out of this?”, usage reporting is where you go to answer them. This lesson walks through what’s available and, more importantly, what to do with it.
The Billing & Usage page is also where you manage and review your billing information:
Past invoices — your full invoice history is listed here. You can view and download past invoices for any billing period directly from this page.
Current billing period charges — if your account has entered pay-per-credit billing, the charges accumulating for the current period are visible here in real time, so you always know where you stand before the period closes.
Payment method — you can update your stored payment method at any time by clicking the Edit link next to the Subscription panel.
Some plans include an embedded analytics dashboard directly on the Billing page. All data updates once per day — the previous day’s data reflects at approximately 3am EST. Everything in the dashboard is downloadable as a PDF, CSV, Excel, or JSON file.
The Usage Summary shows credit trends over time. You can adjust the date range with the Starting Date and Ending Date fields.Includes:
Total credits by day — spot spikes and identify when high-consumption flows ran
Top credit-using users (by percentage) — quickly see if consumption is concentrated with a few people
Total credits by flow — find the most expensive flows in your stack
In practice: If one flow is consuming a disproportionate share of credits, pull this view, identify the flow, and check how often it’s running and how many steps it has. That’s usually where the answer is.
A per-user breakdown — most useful when you want to understand individual activity:
Field
What it tells you
Total flows owned
How many flows this person is responsible for
Total flows owned with AI
Flows that used AI steps in their last run — relevant since AI steps consume credits proportionally
Created flows last 30 days
Measures how actively someone is building
Unique flows run last 30 days
Distinct flows they triggered — gives a sense of daily activity
Total flow runs last 30 days
Total runs including repeats of the same flow
Total credits last 30 days
Their share of overall consumption
In practice: If the Usage Summary shows one user consuming 40% of your team’s credits, the User Report is the next place to look. Sort by credits and investigate what they’re running and how often.
A per-flow breakdown — most useful for identifying high-cost or underused flows:
Field
What it tells you
Unique flow ID
The flow’s internal identifier
Flow name / owner email
Who’s responsible for it
Includes AI
Whether the last run used AI steps — a signal for higher credit consumption
Total runs last 30 days
How frequently the flow is running
Total credits last 30 days
Its share of overall consumption
In practice: Before a renewal or plan review, sort the Flow Report by Total Credits. Flows that are consuming a lot but running infrequently might be good optimization candidates. Flows that haven’t run in 90+ days might be candidates for archiving.
All data reflects the most recent date with activity — updated as of yesterday at midnight UTC. User names and emails reflect the current state of the account; historical name changes won’t appear in past data.
With reporting covered, the next lesson looks at how integrations work — and how to set up authentication in a way that’s scalable and secure for your whole team.
