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Discover
Existing coverage assessed, defect history analyzed and highest-risk areas identified.
Output: documented current coverage and risk profile.
Software Quality Assurance
Continuous verification across the delivery pipeline.
Automated functional, API, performance and security testing, integrated into your delivery pipeline and executed on every build.
What Is Software Quality Assurance?
Software quality assurance is the verification that software behaves as specified before release. It covers test strategy, automation, functional and API testing, performance and security validation, and regression coverage.
Continuous quality engineering executes this verification on every change.
What Defects Cost by the Time You Find Them
$2.41 trillion
Cost of poor software quality to the US economy in 2022.
CISQ, The Cost of Poor Software Quality in the US, 2022
$1.52 trillion
Accumulated software technical debt in the US, measured separately from the annual cost above.
CISQ, 2022
$59.5 billion
Annual cost of inadequate software testing infrastructure to the US economy, with a third recoverable through improved testing.
NIST, Planning Report 02-3
Signs You Need Software Quality Assurance
- Manual Regression Before Every Release
- Test Coverage Without Reporting
- Test Suites Too Unreliable to Act On
- Release Decisions Without Evidence
- Compliance Without Documented Validation
What Software Quality Assurance Covers
Risk-based test strategy defining coverage targets, test levels and quality gates, prioritized by business impact rather than uniform coverage across the codebase.
Automated suites built for maintainability, with stable selectors, isolated test data, and execution integrated into the delivery pipeline.
Verification of application behavior against defined requirements, across user journeys, edge cases, and error states.
Contract testing, schema validation and integration coverage across service boundaries and third-party dependencies.
Load, stress and endurance testing against defined thresholds, with bottlenecks identified before they surface under production traffic.
Vulnerability scanning, dependency analysis, authentication and authorization testing, and validation against OWASP standards.
Automated protection of existing behavior, executed on every change so unintended impact is detected at commit rather than at release.
Quality embedded in the delivery pipeline through automated gates, defect escape tracking, and coverage reporting.
How We Build Test Coverage
Software Quality Assurance runs Design, Build and Launch on The Pivot.
Pipeline integration runs through DevOps Engineering, and application changes required for testability run through Product Engineering.
What You Walk Away With
Verification that runs without anyone remembering to run it.
Automated test suites executing on every change- Documented coverage across functional, API, performance and security testing
- Quality gates enforced in the delivery pipeline
- A test data and environment strategy your team can maintain
- Defect escape rate measured against a baseline
- Test documentation and framework ownership transferred to your team
Our Technology Landscape
Web and mobile automation
- Playwright
- Cypress
- Selenium
- Appium
Unit and integration
- Jest
- Vitest
- JUnit
- pytest
- PHPUnit
API and contract
- Postman
- REST Assured
- Pact
- Karate
Performance
- k6
- JMeter
- Gatling
- Locust
Security and analysis
- OWASP ZAP
- Snyk
- SonarQube
- Burp Suite
Pipeline and reporting
- GitHub Actions
- GitLab CI
- Allure
- TestRail
Common Questions
Coverage percentage matters less than what is covered. Mature teams typically automate 70 to 80 percent of regression, concentrated on the paths that carry business risk.
Yes. Most engagements stabilize and extend what already exists. Replacing a suite is a recommendation we make only when maintenance cost exceeds the value it returns.
Coverage on the highest-risk paths typically lands within 4 to 6 weeks. We sequence by defect history, so the areas that break most often are protected first.
Usually. Flaky tests are almost always caused by timing assumptions, shared test data or environment inconsistency rather than by the application. Stabilization is the first phase of most engagements.
Not entirely. AI accelerates test generation, flakiness triage and visual regression, but it does not own release risk or regulatory sign-off. Automation handles repetition; exploratory and usability testing still require people.
Your team. The framework, documentation and CI configuration sit in your repositories, built so your engineers can extend coverage without us.
Start With a Coverage Assessment
The assessment maps existing coverage against where defects originate and return a prioritized automation plan.
Talk to a QA engineer