QA automation and release engineering for a United States B2B SaaS platform

The client is an Austin-headquartered B2B software company providing a workflow automation platform to mid-market and enterprise customers in North America. At engagement start it had approximately USD 74 million in annual recurring revenue following a Series C round, with an engineering organisation of 88 people. Its growth plan required a material increase in release velocity without a corresponding rise in production incidents.

Release velocity had become the binding constraint on the roadmap. The company shipped approximately 3.6 production releases per month against a target of weekly per-team releases. The bottleneck was a manual regression cycle consuming five to seven days before every release.

Test automation existed but was not trusted. Coverage sat near 36% and the suite carried a flake rate high enough that engineers re-ran failures rather than investigating them, so genuine failures were sometimes dismissed.

Escaped defects were rising with release volume, with seven critical and nineteen high-severity escaped defects in the quarter before the engagement.

Hiring had failed to solve it. Austin QA automation engineers commanded compensation the company found hard to justify against feature hires, and two QA hires had transferred into feature teams within months.

The client selected Corpshore Mexico primarily on time zone and talent. Monterrey shares the full US working day, and its strong engineering labour market supplies QA and release engineering talent at a cost the Austin market could not match. QA is collaboration-intensive, and the client had concluded from a prior offshore experience that asynchronous handover was the root cause of failure.

Corpshore proposed treating the engagement as capability transfer rather than capacity rental, with defined knowledge-transfer milestones, and its proposed lead identified the flake rate rather than coverage as the primary problem during evaluation.

Twenty-four engineers in Monterrey: two technical leads, seven senior, eleven mid-level and four junior, spanning QA automation, DevOps and release engineering. The team works US Central hours, the same clock as Austin, joining standups live. Stack: TypeScript, Playwright, Jest, GitHub Actions, Terraform, AWS, Datadog. All engineers are dedicated to the account.

Fix flakiness before adding coverage. The first eight weeks addressed suite reliability, on the reasoning that adding tests to an untrusted suite compounds the problem. Flake rate fell from 33% to under 3% before coverage work began.

Coverage where risk is. Coverage expansion was prioritised by production incident history and code churn rather than by module.

Progressive delivery infrastructure. Feature flagging and canary release infrastructure decoupled releases from deployments and allowed rollback without a full release cycle.

Documented knowledge transfer. Four defined transfer milestones with documentation and client sign-off ensure the client's own team can operate the pipeline.

Production releases rose from 3.6 per month to 25.2 by month 12. The manual regression cycle fell from five to seven days to under four hours.

Escaped defects fell across every severity band despite the volume increase, with critical falling from seven per quarter to one.

Test coverage rose from 36% to 88% with flake rate held below 3%, and the client's own engineers now extend the suite independently.