Performance engineering · AI automation
For engineering, quality, and operations teams running complex digital platforms. We combine performance engineering and AI automation with test automation, monitoring, and control hubs—so your team can operate with clear, practical evidence.
Capabilities
We help teams make critical platforms resilient under demand, automate complex operational work, and build the engineering foundations that keep delivery moving.
01
Build the evidence to understand capacity, expose bottlenecks, and keep critical platforms resilient under real demand.
02
Apply AI to complex review and operational work, with solutions shaped around your business rules and existing systems.
03
Maintainable front-end and API automation focused on the customer journeys, integrations, and releases that matter most.
04
The data, interfaces, and controls that make automation and validation repeatable across teams and environments.
Test data engineering
Reliable automation and performance validation depend on reliable data. We build the providers, generators, and management workflows that make the right test data available without slowing delivery down.
Explore test data engineering01
Controlled services and interfaces that provide the data your automated journeys, APIs, and performance scenarios need—on demand and in a consistent format.
02
Purpose-built generators for realistic, scenario-specific data, including the edge cases and volume needed to validate how your platform behaves under real conditions.
03
Tailored solutions for preparing, provisioning, refreshing, and controlling test data across teams and environments—bringing visibility and repeatability to a common delivery bottleneck.
Selected outcomes
The work is tailored to each platform, but the objective stays the same: reduce risk, prove resilience, and give teams clear operational confidence.
01
Detected and prevented hundreds of critical customer-journey failures before they reached users.
02
Established performance capacity for major peak events, maintaining zero critical outages under extreme traffic spikes.
03
Built automated production monitoring that runs millions of checks every month.
How we work
The objective is not simply more test scripts. It is a clear, maintainable quality strategy that gives your team useful evidence at every important change.
01
We learn the architecture, dependencies, data, and workflows before deciding what to automate.
02
Frameworks, environments, and test data strategies are tailored to your stack and release process.
03
Clear results help teams identify risk, make decisions, and improve the next release.
AI Automation
We apply AI where it can make complex review work more consistent, traceable, and scalable—while keeping the business rules, evidence, and outcomes in focus.
01
AI-powered analysis designed for Apple and Android applications, helping teams assess marketing content against defined compliance requirements.
02
Automated evaluation and analysis of customer service chats to surface quality, consistency, and actionable service insights.
03
AI-assisted evaluation and analysis of call transcripts, turning conversations into structured evidence for review and improvement.
How the automation works
01 / Source
Collect relevant data from your database, API, or approved external sources.
02 / Analyse
Apply tailored prompts, rules, and context to turn raw information into a consistent evaluation.
03 / Act
Present clear findings and trends so teams can review outcomes and take the next action.
Monitoring tools
We build monitoring around the functions your customers depend on—using real browser journeys and focused uptime checks that turn downtime into an immediate, measurable signal.
Explore monitoring toolsSynthetic journey monitoring
We use Playwright automation to continuously verify critical front-end journeys. Run it from AWS Lambda or a Kubernetes container to fit your infrastructure, schedules, and operational workflows.
Uptime monitoring
Our custom Java framework monitors your core application functions at 15-second intervals, notifies teams about downtime, and calculates the uptime that matters to your service.
Control hubs
We design focused control UIs around the people, workflows, data, and decisions that matter to your team—making complex testing and AI automation easier to run and understand.
Quality operations
A tailored interface for overseeing your testing activity, with the views and controls shaped around your platform, release process, and quality workflows.
AI operations
A purpose-built UI for managing AI automation, reviewing analysis, and turning data-driven outputs into clear, actionable decisions.
Delivery model
From the deployment environment to the ongoing operating model, we shape the engagement around your technical constraints, delivery pace, and in-house capability.
Deployment
Solutions can be deployed in your own infrastructure or in a public-cloud environment, including AWS, Azure, and Google Cloud. The deployment model is selected around your security, operational, and integration requirements.
AI-accelerated engineering
We use agentic engineering tools, including Codex and Claude Code, to accelerate analysis, implementation, and iteration. Experienced engineers retain responsibility for architecture, review, testing, and the quality of every deliverable.
One-off delivery
For a defined project, we can deliver a complete, maintainable codebase with the documentation, deployment guidance, and knowledge transfer your team needs to own it confidently.
Long-term partnership
When your needs evolve, we can stay involved to maintain the solution, extend its capabilities, and adapt it as your platform, data, and operational priorities change.
Consulting
For startups and product teams building or scaling quality, automation, and performance capability. Get experienced technical direction without needing to hire a full leadership team immediately.
01
Define the roles, responsibilities, and operating model for SDET, test automation, and performance engineering teams. Support hiring, interviews, onboarding, and technical mentoring.
02
Decide what to automate, what to measure, and where to invest first—based on your product risk, architecture, release cadence, and growth plans.
03
Build quality checks, performance validation, and useful operational evidence into the delivery process—without creating unnecessary ceremony.
04
Stay involved as an advisor, mentor, and hands-on technical lead while your product, engineering team, and quality capability evolve.
Engineering toolkit
Our tools support the solution; they never dictate it. We select and combine proven technologies according to your platform’s needs.
The team
Emz Systems brings senior technical leadership to performance, reliability, and tailored quality engineering challenges.
Lead Performance Engineer / SDET Lead
With 15 years of experience in quality engineering, performance, and reliability, Michał helps teams build the confidence to release and operate critical systems.
For more than a decade, he has helped assure the performance and reliability of a major e-gaming platform—while designing and delivering tailored automation and reliability solutions for complex technology environments.
Connect on LinkedIn ↗Let’s talk
Whether you are modernising automation, preparing for a high-demand release, or need stronger confidence in critical integrations, start with a focused conversation.
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