Estimate Your QA Costs & ROI in Minutes
Understand the financial impact of your QA strategy as you scale with AI. Make informed decisions based on data, not guesswork.
Uses industry benchmarks for salaries and ROI calculations.
Engineering Team
AI & Development Practices
Product & Quality Requirements
QA Strategy
Testing Volume & Process
Number of new tests created monthly (scales with team size)
Quality Metrics
Percentage of bugs that escape to production
Your Estimated QA Cost & ROI
Estimated Annual QA Cost
$0
Required QA Headcount
0 FTEs
Mix: 0 Manual, 0 Automation/SDET
Estimated ROI
0% - 0%
Expected: 0%
Based on cost savings vs. investment (confidence range).
Est. Bug Cost Savings / Year
$0
From earlier defect detection.
Est. Time-to-Market Gain
~0 Weeks/Year
Faster release cycles.
Interpret Your Results & Plan Next Steps
See how Desplega.ai can reduce your QA costs with AI-powered testing
Calculation Methodology & Assumptions
Results are estimates based on industry benchmarks and may vary based on your specific context, tool choices, and team efficiency. This calculator uses validated formulas from real-world QA teams.
Team & Salary Costs
Base salaries: $90K (Manual QA), $120K (Automation QA/SDET) annually, adjusted for location (0.45x to 1.5x multiplier). Includes 35% benefits overhead, 18% annual turnover, and $18K recruitment costs per hire.
Product Complexity
Simple products (basic CRUD): 30% less QA needed. Complex (multi-tenant, integrations): 30% more. Critical (healthcare, fintech): 80% more. Also determines bug severity distribution - critical products have 15% critical bugs vs 2% for simple products.
AI Coding Assistants
AI increases development velocity but introduces quality issues: 40% more code duplication, 25% more technical debt, 30% more code churn at full adoption. Net result: +18% QA workload despite development speed gains. Junior teams see 35% AI benefit; senior teams see 8%.
Test Automation
Non-linear efficiency gains with diminishing returns. At 30% coverage: ~12% headcount reduction. At 90%: ~58% reduction. Automation maturity matters - low maturity yields 85% efficiency, high maturity (self-healing tests) yields 120% efficiency factor.
Bug Prevention Value
Severity-weighted costs: Critical ($50K), High ($10K), Medium ($2K), Low ($500). Calculator measures incremental savings - bugs that would have escaped to production without QA. Assumes 60% escape rate without QA; your actual escape rate drives calculations.
Time-to-Market
Automation saves 2.5-4.6 weeks per year (logarithmic gains). AI efficiency peaks at ~65% adoption with inverse U-curve. Development velocity multiplier (slow to very-fast) affects final weeks saved. Only 60% of time saved is monetizable due to real-world inefficiencies.
Tooling & Infrastructure
Modern SaaS pricing: $100/month per manual QA, $300/month per automation QA. Platform costs scale with team size. Infrastructure costs adjust for release frequency - daily releases cost 1.6x more than weekly (modern CI/CD reduces penalty vs legacy 3x). Cloud-native assumed.
Regulatory Requirements
Medium compliance (SOC2): +25% QA headcount. High compliance (HIPAA, PCI-DSS, FDA): +50% headcount. Reflects additional testing rigor, documentation, and audit requirements.
Team Experience
Junior teams: introduce 25% more bugs, catch 8% fewer. Senior teams: introduce 25% fewer bugs, catch 12% more. AI coding assistants provide larger productivity gains for junior developers (35%) vs senior (8%).
Maintenance Burden
When test maintenance exceeds 25% of QA capacity, additional headcount penalty applies. Maintenance above 50% triggers warnings. Accounts for time spent updating and fixing test suites vs creating new tests.
ROI Confidence Ranges
Statistical uncertainty modeling (P10/P90 percentiles): Bug costs vary -30% to +50%, time-to-market value ±20%, catch rates ±15%, maintenance efficiency -10% to +15%. Provides realistic high and low bounds, not arbitrary multipliers.
desplega.ai Savings
Competitive offshore rates (0.6x location factor) plus 25% operational efficiency, 50% shared tool license savings, and 35% infrastructure optimization. Compares total cost of ownership vs equivalent in-house team. Payback period accounts for onboarding costs.