Practical Framework for Data Quality Testing Strategy with ISTQB-Based Templates, Real Examples, and Defect Management.

A unified benchmarking framework for evaluating Voice AI agents across conversational quality, audio realism, latency metrics, and safety guardrails with scalable multi-language stress testing.

QA Hub Framework Example: The definitive reference implementation for building scalable, maintainable, and high-performance test suites. Demonstrates best practices in layered architecture, multi-browser support, and CI/CD integration using Python

Production-grade QA framework for Order & Profile Management Systems in prop trading. Tests order lifecycle, execution accuracy, and trading logic correctness across REST APIs, NATS message flows, and PostgreSQL state — built from the ground up with TypeScript, Vitest, and Testcontainers.

QA framework for testing conversational AI systems (LLM agents, chatbots, voice assistants) with workflow validation and regression checks

HealthAPI Quality Assurance Framework

The QA framework for MCP — 46 validators across 8 gates validate MCP servers, Claude skills & extensions before publishing. Schema, security, functional, AI semantic eval, and human review.

Judgment-preserving QA framework for agentic AI systems. v1.0 sealed.