When releases depend on a manual regression cycle, teams ship less often and still find defects in production. We replace that cycle with automated tests at the right layers: unit and contract tests close to the code, a small set of end-to-end flows, and performance and security checks that run on every build.
AI systems need their own discipline. For GenAI and ML releases we build evaluation sets, red-team prompts and regression scoring, so a prompt change or model upgrade is tested as rigorously as a code change before it reaches users.
Test Automation Frameworks
We build automation suites in your stack across API, UI and contract layers, wired into CI. Flaky tests are tracked and fixed, and you get a framework your developers can extend without our help.
Performance Engineering
We model realistic load from production traffic, run load and soak tests with k6 or JMeter, and trace bottlenecks to the query, cache or service causing them. Results are tracked release on release.
Security Testing
We add static analysis, dependency scanning and dynamic testing to the pipeline, and run focused penetration tests before major releases. Findings arrive as prioritised tickets with fixes, not as a PDF.
AI System Evaluation
We build golden datasets, scoring rubrics and red-team prompt sets for GenAI and ML features. Every prompt, model or retrieval change is scored automatically for accuracy, safety and regressions before release.
Test Data & Environments
We create masked or synthetic test data and ephemeral environments per pull request, so tests run against realistic data without copying production records into lower environments.
Howanengagementruns
A typical Quality Engineering engagement runs about 16 weeks from kick-off to a working, handed-over system.
1
Quality baseline
We review defect history, test coverage, release cadence and environments, then map which risks each test layer should catch and where manual effort goes today.
2
Framework and pipeline setup
We set up the automation framework, test data, and CI stages for API, UI, performance and security tests, starting with the highest-risk flows.
3
Regression automation
Sprint by sprint we automate the manual regression pack, retire redundant cases, and add performance budgets and security gates that fail the build when breached.
4
Release gates and handover
We agree release criteria with product owners, publish quality dashboards, and train your developers to write and maintain tests in the same framework.
