Credits

Credits measure the cost of work performed by Dooap Studio.

Credits are billed per Work Unit, not per individual run. A Work Unit groups together all related runs that belong to the same overall piece of work. Credits give teams a simple, consistent unit to track and compare usage across different model types and step configurations.

For example, a Work Unit could include multiple actions that are triggered in a chain, such as OCR and coding automation for a single invoice triggered by invoice import event. The total credits for that Work Unit would reflect the combined cost of all those actions.

Dooap uses a cost plus -pricing to calculate token per credit limits. Token limits are directly proportional to e.g. Azure OpenAI pricing.

Key Principle

Cheaper models → more tokens per credit
More expensive models → fewer tokens per credit

To ensure minimal credit spend, select the most efficient model that can provide the required outcome.

Note that more tailored prompts, while increasing input token spend, may significantly reduce the expensive output token usage. A better prompt may also allow switching to a more efficient model.

What Counts Toward Credits

Each step in a run can consume credits from one or more of these sources:

Input tokens sent to an LLM.
Output tokens generated by an LLM.
OCR pages processed by a document extraction model.
Action run time (measured in seconds).

What Is a Work Unit

A Work Unit is the billing unit for a run or a chain of related runs.

A manual run creates a new Work Unit.
A reprocessed run creates a new Work Unit.
Child actions triggered by another action stay in the same Work Unit.
Error actions triggered during the same chain stay in the same Work Unit.

Example

If Action A is triggered and then triggers Actions B and C, all three runs belong to the same Work Unit.

How Step Credits Are Calculated

For each step, Studio calculates a decimal credit value by dividing actual usage by the per-credit rate of the model or resource:

Step credits =
    (input tokens used ÷ input tokens per credit)
  + (output tokens used ÷ output tokens per credit)
  + (pages processed ÷ pages per credit)
  + (run seconds ÷ seconds per credit)

Each component is only included when both the usage value and the rate are available. For example, an LLM step with no OCR usage skips the pages component entirely.

Example

Suppose an Agent Step processes 5,000 input tokens and generates 4,000 output tokens. The assigned model allows 5,000 input tokens per credit and 2,000 output tokens per credit:

Step credits = (5,000 ÷ 5,000) + (4,000 ÷ 2,000) = 1.0 + 2.0 = 3.0

How Work Unit Credits Are Calculated

Studio first calculates decimal credits for each run step. It then sums all related step credits across the entire Work Unit and rounds up once to the nearest whole number.

The minimum is 1 credit for any Work Unit.
Rounding happens once at the Work Unit level, not separately for each run.

Examples

Work Unit step credits	Sum	Billed credits
1.0 + 2.0	3.0	3
0.5 + 1.2 + 0.6	2.3	3
0.4 + 1.2 + 0.2	1.8	2
0.1 + 0.05	0.15	1
0.0	0.0	1

In the third example, the usage could come from multiple runs inside one Work Unit. The total is still rounded only once after everything is added together.

Where to See Credit Usage

Run details show the Work Unit summary at the top of the page.
Tenant usage reporting shows Work Unit credit usage over time.
Run detail step logs still show token counts and durations that help explain where usage came from.

Use credit data to identify expensive runs, compare model costs, and optimize Action Flows.

Practical Tips

Review credit totals after changing models or adding steps to catch unexpected cost increases.
Use output filters on inputs and tools to reduce token counts, which directly lowers credits.
Run time contributes credits based on wall-clock time for each step, so keep Action Flows efficient.
Compare similar runs to spot regressions in token usage or processing volume.
Credits round up per Work Unit, not per step or per run.
Trigger chains are often cheaper than billing each run separately, because the total is rounded once for the whole Work Unit.

All guides

Credits

Credits measure the cost of work performed by Dooap Studio.

Dooap uses a cost plus -pricing to calculate token per credit limits. Token limits are directly proportional to e.g. Azure OpenAI pricing.

Key Principle

Cheaper models → more tokens per credit
More expensive models → fewer tokens per credit

To ensure minimal credit spend, select the most efficient model that can provide the required outcome.

Note that more tailored prompts, while increasing input token spend, may significantly reduce the expensive output token usage. A better prompt may also allow switching to a more efficient model.

What Counts Toward Credits

Each step in a run can consume credits from one or more of these sources:

Input tokens sent to an LLM.
Output tokens generated by an LLM.
OCR pages processed by a document extraction model.
Action run time (measured in seconds).

What Is a Work Unit

A Work Unit is the billing unit for a run or a chain of related runs.

A manual run creates a new Work Unit.
A reprocessed run creates a new Work Unit.
Child actions triggered by another action stay in the same Work Unit.
Error actions triggered during the same chain stay in the same Work Unit.

Example

If Action A is triggered and then triggers Actions B and C, all three runs belong to the same Work Unit.

How Step Credits Are Calculated

For each step, Studio calculates a decimal credit value by dividing actual usage by the per-credit rate of the model or resource:

Step credits =
    (input tokens used ÷ input tokens per credit)
  + (output tokens used ÷ output tokens per credit)
  + (pages processed ÷ pages per credit)
  + (run seconds ÷ seconds per credit)

Each component is only included when both the usage value and the rate are available. For example, an LLM step with no OCR usage skips the pages component entirely.

Example

Suppose an Agent Step processes 5,000 input tokens and generates 4,000 output tokens. The assigned model allows 5,000 input tokens per credit and 2,000 output tokens per credit:

Step credits = (5,000 ÷ 5,000) + (4,000 ÷ 2,000) = 1.0 + 2.0 = 3.0

How Work Unit Credits Are Calculated

Studio first calculates decimal credits for each run step. It then sums all related step credits across the entire Work Unit and rounds up once to the nearest whole number.

The minimum is 1 credit for any Work Unit.
Rounding happens once at the Work Unit level, not separately for each run.

Examples

Work Unit step credits	Sum	Billed credits
1.0 + 2.0	3.0	3
0.5 + 1.2 + 0.6	2.3	3
0.4 + 1.2 + 0.2	1.8	2
0.1 + 0.05	0.15	1
0.0	0.0	1

In the third example, the usage could come from multiple runs inside one Work Unit. The total is still rounded only once after everything is added together.

Where to See Credit Usage

Run details show the Work Unit summary at the top of the page.
Tenant usage reporting shows Work Unit credit usage over time.
Run detail step logs still show token counts and durations that help explain where usage came from.

Use credit data to identify expensive runs, compare model costs, and optimize Action Flows.

Practical Tips

Review credit totals after changing models or adding steps to catch unexpected cost increases.
Use output filters on inputs and tools to reduce token counts, which directly lowers credits.
Run time contributes credits based on wall-clock time for each step, so keep Action Flows efficient.
Compare similar runs to spot regressions in token usage or processing volume.
Credits round up per Work Unit, not per step or per run.
Trigger chains are often cheaper than billing each run separately, because the total is rounded once for the whole Work Unit.