This project provides a structured pre-release QA risk review pipeline. It analyzes existing test cases and test results, identifies high-risk areas, coverage gaps, and flaky tests, and produces a concise release readiness report for decision-makers. The focus is not on testing execution, but on risk visibility and release decision support.

Public OSINT-based pre-release decision risk assessment of Perplexity AI, focused on observable output behavior, source signaling, uncertainty framing, and decision impact.

Quality gates for definition of done and release readiness.

A practical framework for AI release readiness, risk gating, and accountability in regulated and safety-critical systems.

Eliminating black box risk in outsourced software delivery through governance, visible QA, clear handoffs, and weekly reporting.

solo localization effort, moving text from: write → translate → QA → ship

Public preview of the Application Performance Testing Readiness Checklist. Demonstrates the structure, gating model, and evidence-driven validation approach for PT cycles and test runs. Get the full professional package here: [https://akhileshsarfare.gumroad.com/l/qwoxu]