Credit Usage

How credits are consumed across different platform features: interviews, analysis, and deliverable generation.

Credits are consumed when you use AI-powered features. Here's how usage breaks down.

Credit usage breakdown showing relative cost of each AI-powered feature

What Consumes Credits

AI Interviews

Conducting voice interviews is the primary credit consumer. Credit cost depends on:

  • Interview duration
  • Language processing complexity
  • Real-time AI follow-up generation

Process Analysis

Generating process maps and schemas from interview data consumes credits based on:

  • Number of interviews being synthesized
  • Complexity of the processes discovered
  • Number of cross-functional handoffs identified

Opportunity Scoring

Running the AI analysis to score process steps for automation potential. Cost scales with:

  • Number of process steps being evaluated
  • Depth of the feasibility analysis

Recommendation Generation

Creating 3-tier implementation recommendations consumes credits based on:

  • Number of opportunities being analyzed
  • Detail level of cost projections and architecture guidance

Agent Brief Generation

Producing structured agent briefs for identified opportunities.

Checking Costs Before Actions

Before performing any credit-consuming action, the platform shows:

  • The estimated credit cost
  • Your current balance
  • Whether you have sufficient credits

If you don't have enough credits, you'll need to contact your account manager to increase your allocation.

Optimizing Credit Usage

To get the most value from your credits:

  • Upload context documents before interviews to make them more efficient
  • Focus interviews on the most important business functions first
  • Use opportunity scores to prioritize which functions to analyze in depth