> ## Documentation Index
> Fetch the complete documentation index at: https://docs.greenzero.eu/llms.txt
> Use this file to discover all available pages before exploring further.

# Billing & Credits

> Understanding how credits are tracked and billed for AI Engine usage

<Info>
  Credits are the unit of measurement for AI Engine usage within the platform. They are tracked per
  organization and provide a transparent way to monitor and manage your resource consumption.
</Info>

## How Credits Work

Credits represent the computational resources consumed when using the AI Engine. Each organization has its own credit balance that reflects their usage across all projects and team members.

<Steps>
  <Step title="Credit Allocation">
    Credits are allocated to your organization based on your subscription plan or manual top-ups.
    <Check>You can view your current credit balance in the organization dashboard.</Check>
  </Step>

  <Step title="Credit Consumption">
    Credits are consumed whenever you use the AI Engine for tasks such as: - Model training -
    Inference requests - Data processing operations

    <Note>
      Different operations consume different amounts of credits based on their computational
      intensity.
    </Note>
  </Step>

  <Step title="Usage Tracking">
    All credit usage is tracked in real-time and can be monitored through the dashboard.
    <Tip>Set up usage alerts to be notified when your credits reach certain thresholds.</Tip>
  </Step>
</Steps>

## Credit Consumption Rates

Credit consumption varies based on the specific AI Engine operations:

<CodeGroup>
  ```json Inference theme={null}
  {
    "operation": "model_inference",
    "credit_cost": "0.01 credits per request",
    "factors": [
      "Model complexity",
      "Input size",
      "Output tokens generated"
    ]
  }
  ```

  ```json Training theme={null}
  {
    "operation": "model_training",
    "credit_cost": "0.05 credits per training step",
    "factors": ["Dataset size", "Model complexity", "Training duration"]
  }
  ```

  ```json Data Processing theme={null}
  {
    "operation": "data_processing",
    "credit_cost": "0.02 credits per GB processed",
    "factors": ["Data volume", "Processing complexity"]
  }
  ```
</CodeGroup>

## Billing Cycle

<AccordionGroup>
  <Accordion title="Monthly Billing">
    * Credits are billed on a monthly cycle - Usage is calculated from the 1st to the last day of
      each month - Invoices are generated on the 1st of the following month - Payment is processed
      automatically using your stored payment method
  </Accordion>

  <Accordion title="Credit Packages">
    * Standard package: 1,000 credits - Professional package: 5,000 credits - Enterprise package:
      Custom allocation - Additional credits can be purchased at any time
  </Accordion>

  <Accordion title="Unused Credits">
    * Depending on your plan, unused credits may roll over to the next billing cycle - Standard
      plans: Credits expire at the end of the billing cycle - Professional plans: Credits roll over
      for up to 3 months - Enterprise plans: Custom rollover terms available
  </Accordion>
</AccordionGroup>

## Monitoring Usage

The organization dashboard provides detailed insights into credit usage:

<Frame caption="Credit usage dashboard showing consumption patterns">
  <img src="https://mintlify.s3.us-west-1.amazonaws.com/greenzero/images/credit-dashboard.png" alt="Credit Usage Dashboard" />
</Frame>

<CardGroup cols={2}>
  <Card title="Usage Reports" icon="chart-line" href="/account-management/usage-reports">
    Generate detailed reports on credit consumption across projects and time periods.
  </Card>

  <Card title="Billing History" icon="receipt" href="/account-management/billing-history">
    Access past invoices and payment records for your organization.
  </Card>
</CardGroup>

## Optimizing Credit Usage

<Tip>Implement these best practices to maximize the efficiency of your credit usage:</Tip>

* Use development environments for testing before running operations in production
* Optimize model parameters to reduce unnecessary computation
* Implement caching strategies for frequently accessed results
* Schedule batch processing during off-peak hours
* Regularly review usage patterns to identify optimization opportunities

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="What happens if I run out of credits?">
    When your organization depletes its credit balance, new AI Engine operations will be paused
    until you purchase additional credits or your next billing cycle begins (for subscription
    plans).
  </Accordion>

  <Accordion title="How do I purchase additional credits?">
    Additional credits can be purchased through the organization dashboard under "Billing & Credits" →
    "Purchase Credits". Various package sizes are available to suit your needs.
  </Accordion>

  <Accordion title="Can I transfer credits between organizations?">
    Credits are specific to each organization and cannot be transferred between different
    organizations. Each organization maintains its own separate credit balance.
  </Accordion>

  <Accordion title="How are credits calculated for complex operations?">
    Complex operations have their credit consumption calculated based on a combination of factors
    including processing time, data volume, and computational resources required. Detailed
    breakdowns are available in the usage reports.
  </Accordion>
</AccordionGroup>