.oneBuilt by engineers, for engineering leadersStop guessing what to test
Know exactly where your next bug is hiding
We analyze your codebase, architecture, tests, and knowledge base to identify coverage gaps, balance your testing pyramid, and recommend what to test, where, and why — before a single bug reaches production.
The hiring trap
Senior QA Automation engineers cost $80–150K/year, take 3–6 months to hire, and are the first cut in layoffs
Your coverage reports show percentages — but not what's actually at risk in production
Developers write code 10x faster with AI. Your testing strategy is still stuck in 2019
No one on the team knows where the testing pyramid is broken — until something breaks in production
AI-powered intelligence that replaces the guesswork
Analyzes your codebase, architecture, existing tests, and knowledge base — not just coverage percentages
Balances your entire testing pyramid: unit → integration → E2E — and shows exactly where it's broken
Shift-left by design: generates test cases from requirements and specs, before the feature is even built
Recommends what to test, where, and why — in seconds, not sprint planning meetings
From code to coverage in 3 simple steps
Connect Your Codebase
Integrate with GitHub, GitLab, or Bitbucket. QAntum reads your source code, existing tests, architecture, CI configs, and documentation to build a full picture of your quality posture.
Get Your Test Strategy Map
See your entire testing pyramid visualized. QAntum identifies what's covered, what's at risk, and what's completely missing — then prioritizes recommendations by business impact and risk score.
Generate Tests Before You Code
Use AI-generated test cases to start testing from requirements — before implementation begins. Or generate tests for existing gaps with one click. Watch your pyramid balance in real-time.
See your ROI before you commit
Drag the slider to see how QAntum pays for itself. Calculate savings based on your team size, current QA costs, and release frequency.
Monthly Cost Breakdown
Your Current Costs
With QAntum
Based on $11K/mo engineer cost, 25% testing time, 40% effort reduction, 35% QA optimization
The average mid-size team recovers their investment in under 8 weeks.
How QAntum compares
| Capability | QAntum | Coverage Tools SonarQube, Codecov | AI Assistants Copilot, Qodo | Test Automation Mabl, Katalon, QA.tech | Test Management TestRail, Xray | Hiring Senior QA |
|---|---|---|---|---|---|---|
| Analyzes full codebase & architecture | Static rules | Single file | (manually) | |||
| Balances the testing pyramid | If experienced | |||||
| Identifies real coverage gaps | Shows % only | Exploratory | Partial | (slowly) | ||
| Recommends what to test & why | AI-powered | (subjective) | ||||
| Shift-left: tests before code | From requirements | |||||
| Integrates knowledge base & docs | If has access | |||||
| Annual cost | From $6K/yr | $0–5K/yr | $240–468/yr/user | $1.2–10K+/yr | $1.2–9K/yr | $80–150K/yr |
Built for engineering leaders who are tired of guessing
QAntum is currently in Early Adopters program. We are our own first customer, using our platform to test and validate our own product. Want to be one of the first?