Ship with confidence — backed by a QA powerhouse that writes code, not just tickets. From manual exploratory testing to AI-driven autonomous test agents, our SDETs engineer quality into every stage of your delivery pipeline — across any device, platform, and digital ecosystem.
Whatever your release looks like, QCerris covers the full testing spectrum end to end. Every discipline below is delivered by embedded SDETs who understand your code, your risks, and your roadmap.
Manual & automation, UAT, usability, data, security, compliance, risk-based, and regression testing — coordinated under a single quality strategy.
A product that underwent robust quality management can be launched with confidence — no fear of data leakage or system breakdown. QA not only earns you five-star reviews, it keeps you compliant, improves operational performance, and dramatically reduces development costs.
QCerris has always kept quality assurance as an integral part of product delivery. We offer both stand-alone and full-cycle QA, carried out by a dedicated team of QA engineers, SDETs, test analysts, and managers.
Robust QA gives you a launch with confidence — no fear of data leakage, outages, or breakdowns reaching your users.
Good UX goes a long way, but a bad one goes even longer. Prioritizing QA shows you genuinely understand your users' needs.
Defects caught early cost ~10× less to fix than after deployment. Consistent QA prevents expensive post-launch fires.
Maintainable frameworks with the same engineering rigor as application code — versioned, reviewed, and refactored.
Embedded in sprint planning and code review, catching defects in the design and PR stage — not at the end.
Tests run on every commit, gated deploys, flaky-test triage, and quality dashboards wired into the pipeline.
Modern quality is a software discipline. A Software Development Engineer in Test (SDET) builds the tooling, harnesses, and automation that make quality measurable and continuous — writing real code that lives alongside your application, in the same repo and the same pipeline.
That means test architecture decisions, custom test data factories, API and contract test suites, performance harnesses, and self-healing automation — all engineered to scale with your product instead of breaking under it.
Our team can test from any device, any place, and in any digital ecosystem — combining deep automation expertise with the newest AI-assisted techniques.
End-to-end validation that features work exactly as specified — across user scenarios, edge cases, and structured exploratory sessions.
Robust, maintainable automation frameworks. Our SDETs write code — not throwaway scripts — integrated directly into your CI/CD pipeline.
Autonomous test generation, self-healing suites, and AI defect prediction using Mabl, Testim, Applitools, Functionize, and Playwright + AI.
System behavior under real and peak load with k6, Gatling, and JMeter. SLA and capacity validation before every release.
REST and GraphQL validation with Postman, REST Assured, and Karate. Consumer-driven contract testing with Pact for microservices.
OWASP-based vulnerability and penetration testing for web and APIs, with DevSecOps integration to catch issues before production.
AI visual regression with Applitools, cross-browser/device coverage on BrowserStack and LambdaTest, and WCAG accessibility compliance.
Native and hybrid apps on iOS and Android with Espresso, XCUITest, Detox, and Appium — on real devices and cloud grids.
Validating pipelines, transformations, and warehouse integrity — row counts, schema drift, and data-quality assertions at scale.
Controlled fault injection and resilience testing to prove systems degrade gracefully and recover under real-world failure.
Risk-based and compliance testing aligned to ISO/IEC 27001 practices, plus structured user acceptance testing with your stakeholders.
Test strategy design, QA maturity assessment, tooling selection, and building a quality-first engineering culture in your org.
AI is the fastest-moving area of engineering, and testing is where it pays off first. We use it to expand coverage, cut maintenance, and find the defects traditional suites miss — without replacing engineering judgment.
AI proposes test cases from requirements, user stories, and recorded flows — accelerating coverage of paths humans overlook.
Locator and selector drift is auto-corrected at runtime, slashing the maintenance tax that kills most automation efforts.
Perceptual diffing catches rendering and layout regressions across browsers and viewports that pixel comparison misses.
Risk models flag the modules most likely to break from a change set, focusing regression effort where it matters.
Synthetic, privacy-safe data generation for realistic, repeatable scenarios — without exposing production records.
Structured evaluation, red-teaming, and regression of AI features — prompt versioning, drift detection, and quality scoring.
Our SDETs combine classic test design with modern software and AI engineering capabilities.
Our SDETs stay current with the fastest-moving area of engineering. This is the actual toolset our team works with.
Project analysis, testing goals, scope, and risk profile defined up front.
A test strategy matched to your release cadence, risk, and compliance needs.
Framework implemented and wired into CI/CD for continuous testing.
Requirement checks, bug-fix validation, and regression on every change.
Ongoing maintenance, AI defect prediction, and quality-metric visibility.
Consultation is free. Our QA team is ready to talk.
Let's talk QA