From test automation strategy and CI/CD quality gates to API testing, performance engineering, security testing, and QA team enablement — Cinovic embeds quality into every stage of your software delivery pipeline so bugs become exceptions, not the norm.
We partner with product and engineering teams who are tired of late-night production incidents, manual regression cycles that block releases, and low developer confidence in their own codebase — and are ready to build quality into the way they work, not bolt it on at the end.
We don't just write tests — we engineer quality into your software delivery culture, your CI/CD pipelines, and your team's daily habits so quality stops being a bottleneck and becomes a competitive advantage.
We combine testing expertise, software engineering discipline, DevOps culture, and AI-powered tooling to build quality systems that catch defects earlier, run faster, and give your engineering team the confidence to deploy any time — not just on Friday afternoons when you're feeling brave.
Catch unintended visual changes across your entire UI — pixel-level visual comparison with Percy, Chromatic, or Playwright's built-in screenshot comparison; cross-browser testing on Chrome, Firefox, Safari, and Edge via BrowserStack or Playwright multi-browser support; responsive design breakpoint testing across device viewports; and visual regression alerts integrated into pull request workflows.
Accelerate test creation and reduce maintenance burden with AI-augmented testing — Copilot and LLM-assisted test case generation from user stories and API specifications, self-healing test automation that adapts to UI changes automatically (Testim, Healenium), AI-powered flakiness root cause analysis, intelligent test selection for impact-based regression (Launchable, Sealights), and natural language test specification with tools like Cucumber AI.
Validate system resilience before failures find you in production — chaos engineering experiments with Chaos Monkey, AWS Fault Injection Simulator, or Gremlin; network partition testing; dependency failure injection; database connection exhaustion tests; memory pressure and CPU spike simulation; and GameDay exercises that verify your on-call runbooks and incident response procedures under controlled conditions.
Extend quality assurance beyond pre-production — synthetic monitoring with Playwright or Checkly for continuous production smoke testing; real user monitoring (RUM) for performance anomaly detection; error rate and p95/p99 latency alerting with SLO definitions; distributed trace-based quality analysis with Jaeger or Zipkin; and canary deployment quality gates that automatically roll back on quality regression.
Catch unintended visual changes across your entire UI — pixel-level visual comparison with Percy, Chromatic, or Playwright's built-in screenshot comparison; cross-browser testing on Chrome, Firefox, Safari, and Edge via BrowserStack or Playwright multi-browser support; responsive design breakpoint testing across device viewports; and visual regression alerts integrated into pull request workflows.
Accelerate test creation and reduce maintenance burden with AI-augmented testing — Copilot and LLM-assisted test case generation from user stories and API specifications, self-healing test automation that adapts to UI changes automatically (Testim, Healenium), AI-powered flakiness root cause analysis, intelligent test selection for impact-based regression (Launchable, Sealights), and natural language test specification with tools like Cucumber AI.
Validate system resilience before failures find you in production — chaos engineering experiments with Chaos Monkey, AWS Fault Injection Simulator, or Gremlin; network partition testing; dependency failure injection; database connection exhaustion tests; memory pressure and CPU spike simulation; and GameDay exercises that verify your on-call runbooks and incident response procedures under controlled conditions.
Extend quality assurance beyond pre-production — synthetic monitoring with Playwright or Checkly for continuous production smoke testing; real user monitoring (RUM) for performance anomaly detection; error rate and p95/p99 latency alerting with SLO definitions; distributed trace-based quality analysis with Jaeger or Zipkin; and canary deployment quality gates that automatically roll back on quality regression.
We work with the leading test automation frameworks, performance testing tools, security testing platforms, accessibility validators, and CI/CD quality gate tooling — selecting the right combination for your technology stack, team skills, and quality goals.
Playwright | Cypress | Selenium WebDriver | WebdriverIO | Puppeteer | TestCafé | Katalon | Nightwatch.js | Taiko | Robot Framework | BDD: Cucumber | SpecFlow | Behave
Postman | Newman (Postman CLI) | REST Assured | Supertest | Karate DSL | Insomnia | Bruno | Pact (consumer-driven contract testing) | Spring Cloud Contract | Hoverfly | WireMock | GraphQL Testing: Apollo Testing Library | gRPC testing tools
k6 | Gatling | Apache JMeter | Locust | Artillery | Taurus | NBomber (.NET) | Vegeta (Go) | Datadog APM | New Relic | Grafana | Prometheus | AWS X-Ray | Jaeger | Zipkin | Checkly (synthetic)
OWASP ZAP | Burp Suite | Snyk | SonarQube | Checkmarx | Veracode | Semgrep | Trivy | Grype | GitLeaks (secrets detection) | OWASP Dependency Check | npm audit | pip-audit | Nuclei | SQLMap
Stay ahead with practical guides, framework comparisons, and case studies on test automation, shift-left quality, performance engineering, CI/CD quality gates, and building engineering teams that ship with confidence.
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Tell us about your product, your users, and the experience problems you're seeing — drop-off rates, confusion, low adoption, or conversion shortfalls — and we'll give you an honest UX assessment and a prioritised improvement roadmap.
Traditional QA (Quality Assurance) is a gate at the end of development — testers verify the software works before release. Quality Engineering is broader and more proactive — it embeds testing throughout the entire development lifecycle (shift-left), automates quality checks in CI/CD pipelines, involves engineers in writing tests alongside production code, and treats quality as an engineering discipline rather than a separate function. Quality Engineering catches bugs at 10× lower cost and enables faster, more confident releases.
Playwright is the modern standard — fastest execution, built-in multi-browser support (Chrome, Firefox, Safari, Edge), excellent debugging tools, and strong TypeScript support. It's our default recommendation for greenfield automation projects. Cypress is excellent for React-based web apps and developer-experience-focused teams — but limited to Chrome-based browsers and single-tab testing. Selenium remains relevant for legacy environments requiring Java/Python/.NET integration or cross-browser coverage on older browser versions. For new projects, choose Playwright. For existing Cypress suites, keep iterating. For Selenium, plan a migration.
Shift-left testing means moving quality activities earlier in the development process — writing tests before or alongside code, conducting design reviews for testability, automating quality checks in pull requests rather than waiting until release, and giving developers immediate feedback on test failures. It matters because defects found in production cost 100× more to fix than defects caught in development. Shift-left reduces that cost, shortens feedback loops, and builds developer confidence in the codebase they're working on.
A focused automation suite for a single critical user journey (e.g. checkout or onboarding) takes 3–5 weeks, including framework setup. A comprehensive E2E automation suite covering 20–30 key user flows takes 8–14 weeks. A full test automation programme covering E2E, API, unit, and performance testing with CI/CD integration typically takes 4–6 months for a mid-size application. QA transformation engagements — changing a team's entire testing culture and tooling — run 3–6 months. We scope everything during your free QA health check.