IntelliCorp (Tricentis LiveCompare)
AI-powered impact analysis and automated DevOps for SAP ecosystem optimization.
The Autonomous Quality Engineering Platform for High-Velocity Software Teams.
Mocha is an advanced AI-driven quality engineering platform designed to replace legacy brittle automation frameworks. Built on a proprietary Large Language Model (LLM) architecture optimized for DOM (Document Object Model) interpretation, Mocha allows engineering teams to author end-to-end tests using natural language. Unlike traditional Selenium or Playwright-based tools that rely on fragile CSS selectors or XPaths, Mocha’s engine understands the semantic intent of UI elements, enabling 'self-healing' capabilities that automatically adapt to UI changes without human intervention. By 2026, Mocha has established its market position as the premier 'Zero-Maintenance' testing solution for enterprise web applications. Its technical architecture features a headless execution environment that processes visual and structural data in parallel, ensuring high-fidelity regression testing at a fraction of the traditional computational cost. The platform's 2026 roadmap focuses on 'Predictive QA,' utilizing historical commit data to automatically generate test cases for the most vulnerable code paths before they are even deployed to staging.
Uses LLMs to identify UI components based on their function rather than technical attributes like IDs or classes.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
When a test step fails due to a UI change, the AI re-evaluates the DOM to find the most likely replacement element.
Combines pixel-diffing with AI-driven layout analysis to distinguish between intentional design changes and bugs.
Translates English prompts into executable JSON-based test scripts using a fine-tuned GPT-4o variant.
Analyzes code diffs via Git integration to suggest which tests are most critical to run for a specific PR.
Deep-level traversal of encapsulated Web Components that standard automation tools often fail to access.
Automatically re-runs failing tests in isolated environments to determine if the failure is code-related or environment-related.
Complex multi-step checkouts often break when marketing adds tracking pixels or UI banners.
Registry Updated:2/7/2026
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Testing file uploads and dynamic form fields across different browsers and regions.
Ensuring that data visualizations and charts render correctly across different viewport sizes.