Tricentis launches enterprise agentic software quality platform to support development

Tricentis has launched its unified, agentic software quality platform supported by the new Tricentis AI Workspace. By orchestrating a team of intelligent AI agents, the new platform empowers enterprise teams to deliver rapid innovation while managing risk and resources, fundamentally redefining how high-quality code can be tested, governed, and released at the speed of AI. Tricentis is a global provider in agentic software quality.

The Tricentis Agentic Quality Engineering Platform integrates AI agents with established Tricentis expertise and proprietary technologies across nearly 200 ERPs and packaged applications. It also provides support for web and custom applications. This enables the autonomous acceleration and scaling of software development and quality processes. While ensuring human employees continue to exercise oversight, judgment, and accountability.

Tricentis AI Workspace operates as a single, unified command centre with shared context, integrated workflows. Its native agent-to-agent collaboration is to serve as the system of record and ‘control tower’ for agentic quality engineering. Thus, co-ordinating AI agents across testing, automation, performance and quality intelligence, while embedding governance, approvals and auditability directly into execution.

Kevin Thompson, Chief Executive Officer at Tricentis suggests, “AI is transformative in its ability to create code at unprecedented speed. However, the friction caused by lack of confidence in the quality of the output is causing CIOs real pain. While enterprises demand speed, they also can’t afford to introduce risk through unsecure or low-quality AI-generated code.

“That’s the problem Tricentis is solving. We’re offering the first end-to-end agentic software quality platform that redefines how enterprise software can be tested, governed, and released. To deliver high-quality code at the speed of AI while safely accelerating time-to-value.” 

According to David Cowell, VP of AI and Machine Learning at Tricentis, “We’re already using agentic testing at Tricentis. We are experiencing real impact in our transformation projects. A cloud migration that would typically take a few months took us just one week with agentic AI. That’s the kind of step-change enterprises need. Compressing release cycles without increasing risk and enabling teams to move faster without cutting corners on quality.”

Meet the agents

Within Tricentis AI Workspace are several AI agents working together with defined responsibilities across the entire software development lifecycle (SDLC):

• Tricentis Agentic Quality Intelligence: Continuously interprets change, risk, and quality signals across the SDLC to determine release readiness. The solution automatically directs testing and escalating to humans only when judgment is required.
• Tricentis Agentic Test Automation (updated): Building on the initial launch of Agentic Test Automation, this next generation increases productivity. New features include support for SAP GUI and web applications, deeper integration with Tricentis Tosca automation engines. The solution’s intelligent reuse of test modules is designed to reduce duplication, maintenance, and risk.
• Tricentis Agentic Performance Testing: Delivers enterprise-ready, AI-driven performance validation by embedding autonomous agents across analysis, design, and execution – accelerating insights by around 90–95%. This eliminates manual expert bottlenecks, and enables faster, more confident AI-era release decisions from API to end-to-end systems.
• Tricentis Agentic Test Creation: Integrated deeply into Tricentis qTest, Agentic Test Creation lives side by side with test engineers. This helps them with in-context test authoring. It enables natural-language test creation, allowing teams to generate reusable test cases faster and more consistently while reducing duplication and reliance on specialised expertise.

These agents and the capabilities they unlock represent the foundation of a broader agentic quality platform. Solutions designed to evolve as enterprises move toward fully autonomous, continuously governed quality engineering over the next several years.

Benefits include:

• Faster quality throughput at enterprise scale: Orchestrates AI agents, tools, and workflows to eliminate manual handoffs and enable continuous quality execution as delivery speeds increase, with early deployments achieving up to 60% automation of regression test grids.
• Operational control and governance over AI: Centralizes policy enforcement, approvals, and auditability, giving leaders visibility into what AI is doing and when human intervention is required.
• Lower-risk AI adoption: Embeds human review gates and oversight into execution so enterprises can scale AI without increasing compliance or operational risk.
• Accessible AI across quality teams: Enables zero-code creation and management of AI agents so teams can scale AI consistently without specialized skills or custom development.

Enterprise Times: What this means for businesses

The current global interest in AI will inevitably accelerate both the pace and scope of change among the countless applications that comprise modern enterprise landscapes. Errors in even a single application can quickly cascade throughout an organization’s connected application ecosystem, increasing downtime, introducing risks, and derailing business objectives.

Generic AI tools may appear smart and fast, but without a complete understanding of specific application context and critical end-to-end application connections, results can be unreliable and risky.

Software development used to be such a human labour intensive, delicate activity, with incorrect coding causing immeasurable technical headaches. Hence the early adoption of AI across the software development lifecycle. The Tricentis AI Workspace marks an interesting shift by enabling orchestration throughout this lifecycle. Beyond just code generation or test automation.

As AI speeds up software creation, trust becomes essential — software may be close, but not yet production-ready. Tricentis solution sounds attractive. Moving from manual testing to confidence engineering, with agents that identify unknowns, prevent defects, manage risk-based validation. The platform offers readiness signals to guide decisions.

This helps customers leverage AI speed while minimising risk and boosting release confidence. Tricentis says this achieves greater ROI through faster delivery and ongoing learning. So, look forward to reading future glowing use case and testimonials to this effect in a few months time.

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