Mike Bennett

Case study

Software Development Firm · Multi-project delivery — Ongoing

One QA standard across as many as nine client projects at once

A full-service software development firm was shipping web, mobile and custom software for clients with no standardized QA process. Several of those projects were high-stakes systems where a defect is measured in hours, not tickets.

Up to 9

concurrent client projects

~50%

estimated faster test execution

1

standard QA process across every project

Context

The firm builds custom software for clients across several industries, including systems that handle sensitive personal data and have to perform when people depend on them most.

Risk

With a growing, multi-location workforce, teams across the firm had naturally developed their own testing approaches, so the priority was bringing them on to one consistent standard. Some projects also carried higher stakes, with sensitive personal data, role-based access and AI-driven features where accuracy and access controls had to be exactly right.

Approach

  1. Helped define a single QA process and set of standards that scaled across projects of very different size and technology.
  2. Stood up shared tooling in Jira, Xray, Confluence and SharePoint so test evidence lived in one place rather than in individual inboxes.
  3. Tested every user role against every action, confirming people could only see and do what their access allowed. Permissions got their own test suite rather than being assumed to work.
  4. Validated AI-driven features against requirements, confirming their outputs were accurate and reliable before reaching users.
  5. Ensured data integrity and the security of sensitive information on every project.
  6. Load tested with Locust against worst-case traffic spikes, confirming systems held up at peak demand instead of degrading when it mattered most.
  7. Built automated coverage in Playwright, Python and PyTest where it saved time, rather than burning QA hours on automation for its own sake.
  8. Coordinated onshore and offshore teams to keep quality standards consistent across every project.

Result

Test cycle times fell while both coverage and defect detection rates rose.

Evidence

Delivered a test plan, a QA playbook in Confluence, test cases in Xray, defect tracking in Jira, test reports, Playwright automation, Locust load test scripts, test datasets and a UAT test matrix.

Stack

  • AWS
  • Azure
  • Jira
  • Xray
  • Confluence
  • Locust
  • Playwright
  • Python
  • PyTest
  • Postman
  • MySQL
  • Multi-tenant isolation
  • Audit and access control
  • AI-assisted testing