Quality engineering for Agile, DevOps and hybrid teams that want fewer defects and faster releases. PinnacleQM embeds risk-based quality practices, automation and measures into delivery from the first sprint.
30+years of international
IT experience
When testing happens at the end, defects are found late, fixes are rushed and releases slip. Teams know quality should shift left, but without shared practices, skills and measures, it rarely does in practice. The result is predictable: rework, delays and production incidents.
PinnacleQM quality engineers work inside your teams to design risk-based coverage, build automation within sprints, and set quality gates and measures, so defects are prevented or caught early. Quality becomes part of how teams work.
Quality engineering is a way of working. We bring practices, automation and measures that help teams prevent defects rather than chase them.
Aligned with ISO/IEC/IEEE 29119 and ISO/IEC 25010.
Quality starts with requirements and design reviews, not after code is complete. Ambiguities are resolved before they become defects.
Tests focus on the business risks and quality characteristics that matter most. Lower-risk areas receive lighter, faster checks.
Automation is built as features are built, so regression never falls behind. Every sprint ends with its regression already automated.
Quality gates and KPIs show whether each increment is ready to move on. Teams stop debating whether work is done.
Engineers are trained and certified, and coach your teams as they work. Your people gain skills alongside ours.
Retrospectives and metrics drive steady improvement across releases. Changes are based on evidence rather than opinion.
Practices that span requirements, design, build, test and release.
We review requirements, user stories and designs for testability, ambiguity and risk, and agree clear acceptance criteria before development starts, so developers and testers share one understanding and rework falls.
We run product risk workshops and design coverage against ISO/IEC 25010 quality characteristics, so test design follows business risk, not just specifications, and coverage decisions can be explained to stakeholders.
Automation is built alongside features using no-code, natural-language scripts. Modular, reusable tests keep maintenance low, so regression stays current with every sprint and teams avoid building up automation debt across releases.
We define and implement quality gates in your pipeline, so every build is checked automatically, developers get fast feedback and only changes that meet agreed criteria progress towards production and safely.
We plan performance, security, accessibility and resilience testing in proportion to each system's importance and exposure, and log findings in the same backlog as functional defects so they are fixed.
We set KPIs such as defect leakage, critical-risk coverage and automation reliability, and report trends, so leaders can see, in numbers they trust, whether quality is really improving over time.
We work inside your teams, introducing practices gradually and coaching as we go, so delivery keeps moving while quality steadily improves.
Understand current practices, risks, tools and quality measures in each team. Findings shape a practical plan for each team.
Place quality engineers in teams to model risk-based practices and automation. Practices are adapted to how each team works.
Build in-sprint automation and quality gates in the pipeline. Regression is automated inside each sprint.
Track defect leakage, coverage and reliability against agreed targets. Results are reviewed openly with each team.
Coach teams and refine practices through retrospectives and quarterly reviews. Improvements are recorded and their benefits measured.
Enginuity as a service and a team of 12 replaced a 125-person offshore regression team across a Big 4 bank's end-to-end lending systems.
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When a core banking platform was upgraded, Enginuity's machine learning updated the automation in 2 hours and every script ran without test pack changes.
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A state health integration re-platforming was delivered by 7 testers in 12 months against competitor estimates of 40 to 46 testers over 36 months.
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A practical way to decide which regression tests to automate, which to keep manual, and how to measure the return.
Tell us about your teams, delivery method and quality challenges. We will show how quality engineering could reduce defects, speed your releases and build lasting capability in your teams.
Mention your delivery method, team count and main quality issues.
