Section 1: Cost of Failure (Without Evals)
Estimate what it costs when an AI error reaches production.
Monthly Failure Costs
Monthly AI interactions
Total queries/requests your AI handles per month
Current error rate
Percentage of responses with meaningful errors (%)
Avg. cost per production error
Support ticket + customer impact + eng time ($)
Monthly cost of AI failures
$125,000
5,000 errors / month
Section 2: Eval Investment
Estimate the cost of building and maintaining your eval system.
Monthly Eval Costs
Eng hours / month on eval
Building pipeline, maintaining golden set, reviewing results
Eng hourly rate ($)
Fully loaded cost including benefits
LLM-as-Judge API costs ($/mo)
API usage for automated evaluation runs
Tooling / platform costs ($/mo)
Any eval-specific SaaS or infrastructure
Monthly eval investment
$3,600
Section 3: Error Reduction from Evals
Conservative estimates based on production data from teams deploying structured evaluations.
Projected Improvement
Expected error reduction (%)
Typical: 40-60% for structured evals. Conservative: 30%.
ROI Summary
Errors Prevented / Month
2,250
Monthly Savings
$56,250
Net ROI
1,463%
Annual Savings
$631,800
Annual Eval Cost
$43,200
Payback Period
< 1 month
Note: This calculator focuses on direct cost savings. Evals also improve
team velocity (less firefighting), customer trust (fewer visible failures), and compliance
posture—none of which are captured here.
Industry Benchmarks
| Scenario | Avg. Error Rate Before | After Structured Evals | Typical ROI |
|---|---|---|---|
| Customer support RAG | 5-8% | 2-3% | 500-2000% |
| Internal knowledge base | 8-12% | 3-5% | 300-800% |
| Code generation | 15-25% | 8-12% | 200-600% |
| Regulated domain (legal, medical) | 3-5% | 0.5-1% | 1000-5000% |