Credits & Billing
Understand how the monthly AI credit grant works, monitor usage, and data privacy protections.
How AI Credits Work
Your organization's AI credit balance is granted by your subscription plan — there is no separate credit purchase flow. The allocation is a function of your plan tier and the number of seats on your subscription.
- The balance is overwritten on the 1st of every calendar month with a fresh plan allocation.
- Unused credits from the previous month are not carried over — the balance resets, it does not accumulate.
- Credits are not individually purchasable as top-ups; to change your allocation, change your subscription tier or seat count.
- Only credit-consuming AI features (Test Case Generation and the AI Agent) draw down the balance, and they are charged token-based on actual usage. AI Insights reports and AI Score badges consume no credits.
Because credits reset monthly rather than accumulating, size your subscription (tier and seats) for the AI usage your team expects each month. Only Organization Owners and Admins can change the subscription that determines the allocation.
Credit Management
Effective credit management ensures your team always has AI capabilities when needed:
Monitoring Usage
- Balance indicator — The credit balance is shown in the navigation bar when AI is enabled.
- Usage breakdown — View credits consumed by feature type (generation, chat) in the AI settings page.
- Monthly reset — Remember that the balance is replenished on the 1st of each month; usage in the current month draws down that month's allocation.
Controlling Costs
- Disable AI temporarily — Toggle AI off during periods when it is not needed (e.g., between sprints).
- Educate your team — Share guidelines on when AI features are most valuable to avoid wasteful usage.
- Keep AI Agent sessions focused — Long conversations carry more context and therefore use more tokens per message; start a fresh session for unrelated tasks.
- Refine generation prompts — Better descriptions produce better results on the first try, reducing the need for multiple generation attempts.
Data Privacy & Security
TestKase takes data privacy seriously when processing AI requests:
- Encrypted in transit — All data sent to AI models uses TLS encryption.
- Not used for training — Your test case data, descriptions, and project information are never used to train AI models.
- No data retention by AI providers — Data is processed in real-time and not stored by the underlying AI service.
- Organization-scoped — AI features only access data within your organization. There is no cross-organization data sharing.
- Audit trail — AI actions are logged in the activity history so administrators can monitor usage.
If your organization has strict data handling requirements, review the privacy policy and compliance documentation before enabling AI features. You can keep AI disabled and still use all other TestKase features.