Transform your software testing with AI-powered automation. Generate comprehensive test suites, catch bugs before production, and accelerate releases with predictable CAPEX infrastructure.
Enterprise-grade test automation orchestrated through Model Context Protocol (MCP) with multi-agent AI system, Computer Controller for legacy apps, and FDAP analytics stack
Seamless integration with Jenkins, GitHub Actions, GitLab CI, and Azure DevOps pipelines
Local AI processing on NVIDIA, AMD, and Apple MLX hardware for complete data privacy
FDAP stack delivers sub-second query performance on billions of test results
While most AI systems rely on RLHF (just a "vibe check"), our platform implements true reinforcement learning with actual reward signals from test outcomes—the same approach that enabled AlphaGo to beat world champions.
RLHF relies on human labelers selecting what "looks good" rather than what actually works—a proxy objective that doesn't measure real success.
Systems quickly learn to exploit the reward model with adversarial examples that score high but produce nonsensical outputs.
Can only run for a few hundred steps before the model starts gaming the system—not true RL like AlphaGo.
Tests either pass or fail, bugs are found or missed—concrete, measurable outcomes that provide true reward signals, not subjective preferences.
Code coverage, bug detection rates, false positive ratios—quantifiable metrics that can't be gamed like a "vibe check" reward model.
Can run unlimited optimization steps because we're optimizing against real outcomes, enabling AlphaGo-level mastery in test generation.
AI agents create comprehensive test suites based on code analysis
Run tests and collect actual outcomes: pass/fail, coverage, performance
Reward based on bugs caught, coverage achieved, and false positive rates
Update test generation strategy based on actual results, not preferences
Unlike RLHF systems that plateau quickly, our true RL continuously improves, learning optimal test strategies from millions of real test executions—achieving the QA equivalent of AlphaGo's dominance in Go.
Traditional testing approaches are failing to keep pace with modern development cycles, creating bottlenecks that cost enterprises millions in delays, bugs, and technical debt.
Traditional manual testing creates significant delays in release cycles, with QA teams becoming the bottleneck in fast-moving development environments.
Many enterprises run critical business applications on legacy systems that are difficult to test with modern automation tools.
Cloud-based testing services with token-based pricing create unpredictable costs that can spiral out of control during intensive testing periods.
Our agentic AI system transforms software testing by deploying autonomous agents that understand context, learn from patterns, and continuously improve testing strategies—all while maintaining complete data sovereignty with on-premise GPU infrastructure.
AI agents analyze your codebase, business requirements, and user stories to generate comprehensive test suites that understand your domain.
Agents continuously learn from test results, failed scenarios, and production issues to improve testing strategies and coverage over time.
Advanced computer vision capabilities enable testing of legacy applications, complex UIs, and visual regressions without API access.
Comprehensive testing capabilities powered by AI agents with deep learning and continuous improvement.
AI agents analyze your codebase, requirements, and user flows to generate comprehensive test suites automatically.
Computer vision and UI automation capabilities enable testing of legacy applications without API access.
Comprehensive dashboards and reporting provide insights into test coverage, performance, and quality trends.
See exactly how much you can save by switching from unpredictable cloud costs to predictable on-premise infrastructure.
Beyond just a framework - we deliver a fully managed enterprise service with expert integration into your existing CI/CD workflow systems. Backed by industry-leading SLAs and dedicated support.
Seamless integration with Jenkins, GitHub Actions, GitLab CI, Azure DevOps, and other popular CI/CD platforms.
Comprehensive dashboards and reporting tools to track test coverage, performance metrics, and ROI.
Enterprise-grade support with guaranteed response times, dedicated account managers, and custom SLAs.
Infrastructure deployment, CI/CD integration, and team onboarding
First automated test generation and validation with existing test suites
Complete automation rollout across all applications and environments
Our team combines deep AI/ML expertise with enterprise software quality experience to deliver implementations that actually work in production environments.
Over 50+ successful AI implementations in Fortune 500 companies across various industries including healthcare, finance, and manufacturing.
Deep understanding of software testing methodologies, CI/CD pipelines, and quality processes built from years of consulting experience.
Proven methodologies for quick implementation and integration with existing systems, typically achieving ROI within 3-6 months.
We handle the complete implementation process from infrastructure setup to team training, ensuring seamless integration with your existing CI/CD workflows and maximum adoption across your organization.
Complete hardware procurement, installation, and configuration of your on-premise GPU infrastructure.
Comprehensive training programs to ensure your team can effectively use and maintain the AI QA system.
Strategic approach to organizational change ensuring smooth adoption and maximum ROI from your AI QA investment.
Join leading enterprises already saving millions with AI-powered QA automation and predictable CAPEX infrastructure.