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JZ Technology

11 / Quality, cloud & infrastructure

Testing that finds defects before your customers do

From test strategy to automation running in CI — we build a quality process that takes the gamble out of releases.

Defects found by customers are the most expensive kind: they cost trust, urgent fixes and the whole team's evenings. If every release makes people nervous and the list of production bugs grows faster than the list of new features, the problem usually isn't the developers. It's the missing process that catches regressions before users do.

We treat testing as engineering, not clicking through a script. Automated tests are code (Python, PyTest) wired into your CI pipeline; where automation doesn't pay off, we design manual and exploratory testing with a clearly defined scope. You don't get "more testing" — you get a process where it's clear what gets checked, when, and with what result.

The firm's QA practice was built by its founder on enterprise projects — in environments at PwC, Roche and E.ON, where data quality, scale and regulation leave no room for "it'll probably be fine". We apply the same standards at every size, from a startup MVP to systems a company has relied on for years.

What the service covers

  • Test strategy and quality process

    This work ends with you knowing what in your project actually needs testing and in what order. You get a test strategy and plan, test cases and release verification rules — and if a QA process already exists, we audit and improve it instead of rebuilding everything from scratch.

    • Test strategy and plan for a product or release
    • Test cases and checklists
    • Audit and improvement of an existing QA process
    • Defect analysis and triage
  • Deciding what to automate

    We identify which scenarios are worth moving to a suite and which are cheaper left to a person — with an estimate of what each would cost to maintain. Building and maintaining the suite itself is covered by a separate service: test automation.

  • Manual and exploratory testing

    Where automation can't see the problem, a human looks. We run exploratory testing of new features, verify releases before production deployment, test mobile apps and check behaviour across browsers and devices.

    • Exploratory and scripted testing of new features
    • Release verification before production deployment
    • Mobile app testing
    • Cross-browser and cross-device testing
  • API, integration and database testing

    We test whole flows, not just screens: API contracts between systems, end-to-end scenarios spanning several applications, and data quality in databases — consistency, completeness and migration correctness.

  • Performance and accessibility testing foundations

    Baseline performance testing that shows how the system behaves under load and where the bottlenecks are, plus accessibility testing that catches real barriers for users. This is a foundation and a diagnosis — if a project calls for specialised performance engineering, we say so up front.

Typical situations

  • Every release breaks something that used to work, and the team holds its breath at each deployment.

  • You hear about production bugs from customers instead of from your own test process.

  • Your software house is growing and needs QA capacity for a project or part-time, without hiring.

  • There are no automated tests, and a full manual regression pass takes the team days.

What you can count on

  • You know what gets checked, when, and who owns it — a test process with a clearly defined scope.
  • Regressions surface before deployment, not after — automated tests run in CI on every change.
  • A ship-or-hold call backed by evidence — readable test and defect reports instead of gut feel.
  • Tests your team can take over — written like proper code, version-controlled and documented.

Technologies

  • Python
  • PyTest
  • REST API testing
  • SQL
  • GitHub Actions
  • CI/CD

Projects in this area

Selected work where this scope was part of the delivery.

  • Data Reliability Platform

    The most dangerous data failures are silent: jobs finish 'successfully' while the reports show something false. This enterprise platform on AWS catches such inconsistencies daily — automated validation, integration tests and monitoring, with results you can check rather than take on trust. The firm's founder worked on it as an engineer within a larger team, responsible for data-validation automation and testing.

    Automated data validation and testing in an enterprise environment

Questions about this service

Yes — it's a common starting point. We begin with exploratory testing and a short risk analysis: which features earn money, where defects hurt most and what has been breaking so far. That produces a priority map, and only then come test cases and automation, starting with the most critical paths.

We usually recommend both, in different proportions. Automation pays off where the same scenarios must be repeated at every release; manual and exploratory testing works best for new features and usability. We suggest a specific mix after seeing the project, and we're upfront about where automation would not earn its keep.

Yes. We plug into your existing process and tools — the repository, the task board, the communication channels — anywhere from a few hours a week to full project involvement. We work remotely with companies across Poland, and on-site meetings are available in and around Bydgoszcz.

It is, provided it covers the right things. A small smoke and regression suite for the critical paths, running automatically in CI, can pay for itself very quickly. What we don't propose is automating everything: if maintaining a test would cost more than it's worth, we say so.

Related services

  • Test automation

    Automated UI, API and data suites running in CI — built from scratch, or rescued once nobody looks at the red builds any more.

  • Technical audits

    Audits of code, applications, websites, QA processes and infrastructure. Instead of opinions and reassurances, a written report with priorities and an action plan.

  • DevOps and cloud

    CI/CD, Docker, Terraform and AWS, so releases become a single click and you hear about failures before your customers do.

Let's talk about the quality of your releases

The first conversation is free. Tell us how testing works in your project today and you'll get a concrete answer: what we'd do, what it may cost, and where to start — from a one-off release verification to an ongoing QA engagement. The decision stays with you.