About

Release-risk support for SaaS teams that need stronger QA coverage

TestVector provides QA/SDET review, implementation, and handoff for SaaS teams that need fewer release surprises. The work focuses on how your product is built, checked, and shipped before adding the right checks around the gaps.

Credibility

Why TestVector fits this work

TestVector is led by Denis Tikhomirov and built on 6+ years of QA/SDET work across products where missed issues can create bad reports, wrong data, support escalations, and rushed fixes. The work covers product review, test planning, automation, database checks, file and report validation, CI, and release support.

TestVector focuses on systems where failures hide behind passing UI checks, existing database records, generated files, stale pipeline outputs, and CI runs that look green without proving the right behavior.

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Working style

Clear technical ownership from review through handoff
Practical recommendations without process bloat
Risk-first test planning
Automation only where it proves useful behavior
Clear documentation and handoff
Comfortable working across UI, API, database, files, and CI
Skeptical of test-count theater

Engagement model

How the work usually runs

Review: learn how your product is built, checked, and shipped.

Findings: show what is covered, what is missed, and what should be fixed first.

Implementation: add or improve the checks that make sense for your product.

Handoff: leave documentation, examples, and a setup your team can maintain.

Accountability

How TestVector takes responsibility

TestVector does not stop at a list of observations. The work connects findings to fixes: the workflows to check, the layer where each check belongs, the automation or validation needed, and the handoff your team needs to keep the coverage useful.

Clear scope before work starts
Findings tied to implementation options
Practical fixes, not only recommendations
Documentation your team can keep using
Follow-up support available when the release risk continues

Technical range

Playwright UI automation, API verification, SQL/database validation, file and report validation, CI/CD test execution, Allure reporting, synthetic test data, test suite cleanup, QA strategy, and release-risk review.

Playwright UI automationAPI verificationSQL/database validationfile and report validationCI/CD test executionAllure reportingsynthetic test datatest suite cleanupQA strategyrelease-risk review

Who TestVector works with

The strongest fit is a team that keeps getting surprised after release.

TestVector is most useful when test count is not the hard part. The hard part is knowing what the system supports, where failure would hurt, and which checks create false comfort.

SaaS teams scaling faster than their QA maturity
engineering teams with noisy CI and nervous releases
teams relying on shallow UI-only automation
companies with critical backend, data, reporting, or output workflows
organizations where failures are expensive or difficult to detect
teams that already have tests, but still do not trust releases
startups moving from reactive QA to engineering-grade verification