Delivering fully autonomous, self-adaptive, and context-aware solutions
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Modern testing claims innovation yet fails to deliver real agility and efficiency. This forces enterprises to choose between speed and quality—a choice no one should have to make. We understand this and believe that for actual results, testing needs a complete transformation, not just small improvements.
Our Agentic AI solutions and services promise to transform many aspects of human-machine collaboration with its reasoning and execution capabilities. Optimized for scale, our Agentic AI frameworks accelerate testing, optimize resource utilization, and reduce costs exponentially with the increase in deployed AI agents.
Tx has positioned itself at the forefront of the Agentic AI revolution, ‘testing the limits’ of the power of AI agents to achieve the ultimate autonomous system.
Optimize resource allocation through dynamic scheduling, adaptive test coverage, and AI-powered reporting, ensuring seamless QE lifecycle management.
Leverage AI agents for predictive issue resolution, risk-based testing insights, and self-healing test automation, ensuring proactive incident management in QE.
Implement risk-based assessments and ethical AI consulting to drive responsible, transparent, and high-integrity QE processes.
With a focus on transparency, compliance, and continuous monitoring, we enable responsible AI adoption. Our structured methodology safeguards sensitive data while ensuring AI remains inclusive, accountable, and resilient.
| Agentic QE Solutions | Traditional QE Services |
 Supports all testing specializations without limits |
Limited capacity for specialized testing |
| Automates tests within minutes, reducing costs |
Requires extensive human intervention and maintenance |
| Scales automatically with development pace |
Scales proportionally to headcount |
| Optimized resource usage and cost control |
High operational costs and large teams |
| AI generates tests with SME quality review |
Dependent on humans for test creation |
| Continuously adapts to diverse applications |
Limited adaptability to AI and engineering changes |
| Real-time KPI visualization and updates |
Manual, inconsistent reporting |
| Can be activated or deactivated based on need |
Requires approvals and impacts budget |
| Ensures standardized, AI-ethical compliance |
Dependent on human knowledge, causing standards drift |
Tx is leading the way in Agentic AI-driven QE automation, leveraging autonomous AI agents that don’t just execute tests—they think, analyze, and adapt.
Unlike generic AI automation approaches, we leverage data collected over years in the QE industry to provide you with data-driven and tailored solutions.
As experts in both legacy and Agentic AI-driven ecosystems, we ensure a smooth integration of cutting-edge AI solutions into your existing systems.
Our AI-driven approach isn’t just efficient—it scales exponentially, driving down costs and accelerating testing as your enterprise grows.
Agentic AI refers to AI systems that can act independently to complete tasks, make decisions, and adjust actions based on goals. These systems reduce the need for constant human input or supervision.
Agentic AI improves quality engineering by running tests automatically, identifying bugs faster, and adapting to real-time changes. It reduces manual help, delivers accurate results, streamlining processes, and ensuring robust software performance.
Tx offers Agentic AI solutions in self-healing test automation, ethical AI consulting, and proactive incident management. These services help companies run faster, smarter testing with fewer errors and better outcomes across projects.
Traditional AI follows fixed rules. Agentic AI works independently, adjusts to changes, and learns from tasks. It can plan, decide, and act without help.
Yes. Agentic AI is scalable for large enterprises. It adapts to complex environments, manages multiple test scenarios simultaneously, and learns continuously.
Agentic AI will completely change businesses’ operations—moving from automation to autonomy. In software testing, it will drive self-directed quality engineering, predictive analytics, and real-time adaptation.
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