Representative engagements

Each example describes a common challenge and the way Qanovix approaches it. They are illustrative, and do not describe named clients or quote measured results. Published client case studies will appear here as they are approved.

Representative engagementData Quality

Source-to-Target Data Validation

Challenge
An organization moving reporting to a new data warehouse relied on spot checks of a few records to confirm each load. Differences between source systems and reports were discovered by business users, weeks after the fact.
Approach
Mapping documents were translated into executable SQL validations covering counts, completeness, transformation rules and totals at each layer. Checks were scheduled to run after every load, with results summarized for the data team.
Technologies
  • SQL
  • SQL Server
  • Databricks
  • Python
  • Azure DevOps
Business outcome
Differences are identified at the layer where they occur, before they reach reports, and migration sign-off is based on full reconciliation rather than samples.

Representative engagementTest Automation

Regression Automation Transformation

Challenge
A product team spent several days manually re-checking core workflows before every release. An earlier automation attempt had become flaky and was no longer trusted.
Approach
Automation candidates were prioritized by risk and frequency. Business rules moved to API-level tests, and a small, stable set of browser tests covered critical journeys. The suite was integrated into the CI pipeline with clear reporting.
Technologies
  • Playwright
  • TypeScript
  • REST APIs
  • Postman
  • GitHub
  • CI/CD
Business outcome
Core regression runs automatically on each change, testers focus on exploratory work, and the team can release on its own schedule rather than waiting for a test window.

Representative engagementSoftware Quality

Application Release Quality Improvement

Challenge
A customer-facing application saw recurring defects after releases. Testing happened late, requirements were loosely defined, and go/no-go decisions depended on individual judgment.
Approach
A QA strategy introduced acceptance criteria reviews, risk-based test planning, integration and end-to-end coverage, and a written release checklist with a quality summary for stakeholders.
Technologies
  • Azure DevOps
  • Selenium
  • Postman
  • SQL
  • JMeter
Business outcome
Defects are found earlier in the cycle, stakeholders see the same quality picture before each release, and release decisions are made on evidence.

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