Tricentis, an AI-augmented software quality company, has introduced a unified AI workspace and agentic ecosystem that combines Tricentis’ portfolio of AI agents, Model Context Protocol (MCP) servers, and AI platform services/ The ecosystem aims to provide a centralised hub for managing quality at the speed and scale of modern innovation and support an AI-powered quality engineering.
“AI is reshaping not just how we code, but how we assure quality,” said Eran Sher, chief product officer, Tricentis. “We believe the future belongs to teams that combine human ingenuity with autonomous AI systems, orchestrating quality at every stage of delivery with unprecedented speed, insight and precision.”
Tricentis AI workspace
Tricentis AI workspace, an enterprise-grade environment for managing AI agents, workflows, and governance across the entire software lifecycle, allows organisations to onboard and orchestrate AI agents from Tricentis, partners, or third parties, and to define governance and security policies for responsible AI operations.
The intelligent workspace also claims to integrate directly into SDLC workflows using tools like Jira, GitHub, and ServiceNow; monitor agent performance and compliance through unified dashboards; and scale quality engineering autonomously, empowering teams to manage agentic AI “workforces” while focusing on higher-value initiatives.
The AI workspace unites Tricentis’ agentic portfolio, including Agentic Test Automation (Tosca), Quality Intelligence (SeaLights), Test Management (qTest) and Performance Engineering (NeoLoad), all connected through MCP servers.
