Modern QA services powered by intelligent tools and expert engineers.
of organizations now use AI in software testing workflows
of teams use AI for test case creation; 34.7% for realistic test data generation
faster deployments reported by teams using AI in QA
of GenAI projects will fail due to poor data quality (Gartner)
AI automatically creates comprehensive test cases based on application behavior, user patterns, and business logic, reducing manual effort by 70%.
Advanced ML algorithms identify potential issues before they reach production, with 95% accuracy in predicting critical bugs.
Self-healing test scripts that adapt to UI changes automatically, reducing maintenance overhead by 60%.
AI-powered insights predict testing bottlenecks, resource needs, and quality risks before they impact delivery timelines.
Write test cases in plain English that AI converts to executable automation scripts, making testing accessible to non-technical team members.
AI analyzes code changes and user behavior to prioritize testing efforts on high-risk areas, optimizing test coverage and execution time.
QA is no longer just about writing test cases and reporting bugs. It's about testing smarter, predicting risk, and scaling coverage without bloating the team. AI helps us do that
— Samay Thakkar, Founder and CEO
Discover how we leverage artificial intelligence to transform your testing strategy and deliver superior quality assurance.
We start by understanding your application, key workflows, and areas where AI can add the most value — ensuring alignment with your release goals and business objectives.
Your existing test cases, application flows, and historical defects are gathered to train AI models for better predictions and smarter test coverage optimization.
We configure our AI engines to analyze historical data for risk-based prioritization, suggest new test cases for uncovered scenarios, and identify obsolete or redundant test cases.
AI generates optimized test cases, reducing manual effort by up to 70%. Our experts review and refine AI-suggested tests to ensure accuracy and relevance.
Automated and manual tests are executed in parallel with AI-assisted monitoring, which detects flakiness patterns, correlates failures with recent code changes, and flags likely false positives or critical bugs.
As your application evolves, AI tracks changes and recommends updates or deprecations to your test suite — ensuring tests remain relevant without manual upkeep while providing actionable insights for stakeholders.
95% reduction in manual test case authoring time through intelligent AI-powered test generation and automation
3x increase in regression suite coverage within two sprints using AI-driven test case optimization
70% fewer escaped defects after release through predictive analytics and intelligent bug detection
80% faster QA onboarding for new modules and features with AI-assisted test creation and maintenance
60% reduction in test maintenance overhead through self-healing test scripts and automated updates
90% improvement in test accuracy and reliability with AI-powered risk assessment and prioritization
