Choose an industry sector or functional domain. The top 10 AI use
cases will be pre-loaded — all fields are editable.
Step 2 of 5
Use case volumes
Pre-populated with industry-representative defaults. Edit use case
names, daily agentic interaction volumes, and average token counts per
interaction to match your workload.
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All fields editable — totals computed automatically
Use case daily volumes and average token counts.
Use case
Click to edit the use case name.
Interactions per day
Number of AI agent calls, API requests, or workflow
invocations per day.
Avg input tokens
Average prompt + context tokens sent to the model per
interaction.
Avg output tokens
Average tokens generated by the model per
interaction.
Total tokens per day
Interactions × (Input + Output tokens).
Total (all use cases)
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Total input tokens / day
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Sum across all use cases
Total output tokens / day
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Sum across all use cases
Total tokens / month
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× 30 days
Annualised token volume
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Estimated annual total
Step 3 of 5
Token cost inputs
Enter cloud LLM API pricing for input and output tokens. Use the
quick-fill benchmarks or enter a custom rate.
Input token cost
Tokens sent to the model: prompts, context,
instructions.
Range: $0.15 (GPT-4o mini) → $15 (Claude Opus)
Quick-fill benchmarks
Output token cost
Tokens generated by the model: responses, completions,
reasoning.
Output tokens are typically 3–5× more expensive than input.
Quick-fill benchmarks
Cloud cost preview — based on current volumes
Monthly input cost
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Monthly output cost
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Total monthly cloud cost
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Annual cloud cost
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Step 4 of 5
Breakeven window
Define the investment horizon for the cloud vs on-prem economic
comparison.
