Playwright-based enterprise UI automation combined with GitHub Copilot and Claude-assisted test generation — delivering faster, more reliable, and more maintainable test coverage across every sprint. Our AI-augmented approach reduces manual scripting effort, accelerates coverage expansion, and embeds quality gates directly into CI/CD pipelines so every deployment is validated automatically.
Playwright Framework Architecture — POM-based, sharded, CI/CD-integrated Playwright suites (TypeScript/Python) across Chromium, Firefox, and WebKit — built for low flakiness, high stability, and rapid regression execution in Agile/SAFe programs.
AI-Assisted Test Generation — GitHub Copilot and Claude-assisted test case generation, edge-case discovery, and script maintenance — cutting manual scripting effort and accelerating coverage across complex enterprise and AI-enabled applications.
CI/CD Quality Gates — Automated quality gates integrated into GitHub Actions, Jenkins, Azure DevOps, and GitLab CI — enabling PR-level validation, nightly regression, and release readiness signals without manual intervention.
A national health plan's digital platform serving millions of members across telehealth, claims, benefit verification, and Virtual Primary Care required rapid automation coverage expansion under peak demand. AI-assisted test generation accelerated coverage across iOS, Android, and web. CI/CD-integrated quality gates ensured every deployment maintained the system stability required for uninterrupted healthcare access — while simultaneously validating AI/ML-driven clinical decision support components for prediction consistency and clinical appropriateness across diverse patient populations.
Uninterrupted healthcare access maintained — AI/ML clinical features validated at scaleSpecialist validation practice for AI systems — LLM output testing, RAG pipeline validation, Agentic AI workflow testing, ML model evaluation, and enterprise automation testing. We deliver structured validation frameworks that ensure AI systems are accurate, fair, compliant, and production-ready — grounded in real delivery across insurance underwriting, healthcare decision support, workforce management, and government systems.
LLM & GenAI Output Validation — Hallucination detection, prompt adherence, context relevance, semantic accuracy, toxicity, bias and fairness testing, and guardrail compliance — using RAGAS, DeepEval, and automated evaluation pipelines integrated into CI/CD for continuous model quality assurance.
AI/ML Model Testing — Model behavior validation, output accuracy, precision/recall/F1, training and inference pipeline testing, model regression after updates, and model drift monitoring — delivered across insurance underwriting models, workforce AI systems, and healthcare decision support platforms.
Agentic AI & RAG Pipeline Validation — Tool-calling accuracy, planner-executor loop testing, multi-agent state management, context retention, RAG retrieval quality, faithfulness, and answer relevance — ensuring AI agents behave predictably and safely in regulated production environments.
A top-tier U.S. life insurance company deploying a GenAI-powered policy advisory platform needed quality engineering across two challenges: regression testing a complex enterprise UI suite, and validating LLM outputs for hallucination risk, regulatory compliance, and demographic fairness. RV Tech established a Playwright automation framework with AI-assisted test generation for the UI layer, and a RAGAS-based LLM evaluation pipeline measuring hallucination rate, prompt adherence, and bias across policy recommendation outputs — integrated into a single CI/CD quality gate protecting every production deployment.
60% flakiness reduction in UI suite + automated LLM quality gates in CI/CD pipelineTell us about your program and we'll connect you with the right team within one business day.