QA testing and automation that shortens the path to release

Functional, automated, performance, security, and accessibility QA testing are embedded in our delivery cycle, catching defects early enough to avoid significant rework and retesting.

QA challenges we help you solve

1 Cut manual regression testing down to what requires a human

Automation can cover the repetitive 80%

Test automation frameworks can handle regression testing for every build, which has proven to free up 35% of testing effort in our own AI-native QA program.

2 Confirm your system performs under real load

Load capacity is verified before launch day

Performance and load testing establish how the application behaves at peak traffic, identifying bottlenecks while there's time to address them.

3 Release to every browser, device, and assistive technology

Works where your users are

Compatibility and WCAG accessibility testing span operating systems, screen sizes, and screen readers, so no segment of your audience hits a wall.

4 Understand where your QA process stands

An outside view of your testing practice

A structured QA assessment reviews architecture, processes, tools, and team setup, returning specific recommendations rather than generic advice.

How we approach quality assurance and QA automation

Quality starts at requirements Quality starts at requirements

Our QA engineers join the analysis to flag ambiguous or untestable requirements, removing defects before anyone writes code.

QA automation with a maintenance plan QA automation with a maintenance plan

Our QA experts design test suites to stay stable as your product changes, so you can avoid abandoning fragile automation within a few sprints.

Risk determines the depth Risk determines the depth

Coverage is weighted toward the features whose failure would cost the most, instead of spreading effort evenly across everything.

AI applied to testing itself AI applied to testing itself

Test case generation, documentation, and defect triage are accelerated with AI, which raised documentation speed 60% across nine countries for our own teams.

The practices behind the outcomes

AI-native QA

We can evaluate your existing QA architecture, processes, tools, and teams to plan a transition to AI-native QA.

Functional & Regression Testing

Core functions, interfaces, and data flows are verified against requirements on every release.

Test Automation Engineering

Automation frameworks are built for UI, API, and integration testing across web and mobile.

Performance & Load Testing

Response time, throughput, and stability are measured under expected and peak conditions.

Security Testing

Vulnerabilities in authentication, data handling, and input validation are identified before release.

Accessibility & Compatibility Testing

Applications are checked against WCAG and across browsers, devices, and operating systems.

Built to pivot without losing velocity

We understand that in a high-growth business, pivots are inevitable. We’re built to absorb the impact and keep you moving forward.
arrow-forward Partner with us

QA engineers who leave no stone unturned

Our AI-native QA practices support a global team of hundreds of QA engineers across nine countries.

Case Studies

How Coherent Solutions adapted QA delivery for an AI-driven world PREVIEW
Technology & SaaS

How Coherent Solutions adapted QA delivery for an AI-driven world

As part of a company-wide AI-native software delivery transformation initiative, and using its Continuous Delivery Loop operating framework, Coherent Solutions modernized its global QA delivery function using AI tools and workflows.
360+
QA engineers
50%
less test-case writing effort
60%
improved documentation speed

Ready to reimagine your QA practices?

Our global team of QA engineering experts can set you on the AI-native QA path.

Relevant
Questions

Automate regression, API, and repeatable checks; keep humans on exploratory, usability, and new-feature testing. Automating everything produces brittle suites; automating nothing makes release cycles unsustainable.

Logic at the unit level, contracts and integrations at the API level, and critical user journeys at the UI level. Inverting that pyramid produces slow, fragile suites that catch problems late.

Test case generation from requirements, documentation, and defect triage are getting faster, which shifts QA time toward test design and judgment. The tool's output still needs review before it's trusted.

When defects keep escaping despite testing efforts, when release cycles are slowing, or when automation exists but nobody trusts it. An outside review usually finds process gaps that the team has normalized.

Automated scanning in the pipeline on every build, with periodic manual penetration testing for high-risk areas. Treating security as a one-time audit leaves the gap between audits unprotected.

Defect escape rate to production, time to detect, and the percentage of defects found before code review. Test case counts and pass rates say little about whether the right things are being tested.