The webinar aimed to demonstrate how UiPath Test Cloud leverages AI-driven agentic testing to
Accelerate test design, planning, and execution (e.g., reducing days to hours).
Democratize testing by enabling non-technical users to build and run automations.
Integrate AI for autonomous testing, self-healing workflows, and semantic validations.
Company: UiPath (sponsor of the webinar).
Presenter: Michael LaRue, Director of Sales Engineering for UiPath’s Test Automation Practice.
UiPath Test Cloud combines AI agents, RPA, and low-code automation to
Test AI-powered apps: Validate outputs using NLP models (e.g., cosine similarity, Jaccard index).
Autonomous Testing: Agents explore apps and generate test cases without manual coding.
Self-Healing: Bots adapt to UI changes and escalate exceptions to humans.
Cross-Platform Support: Web, mobile, desktop, SAP, mainframes, and APIs.
Agent Builder: Create custom AI agents (e.g., data retrievers, bug consolidators) using natural language.
Autopilot: Conversational AI to trigger agents and analyze results.
Heatmaps & Change Impact: Auto-generate test cases for SAP transports.
AI Capabilities:
Semantic assertions using NLP (Word2Vec, GloVe).
Autonomous test generation and execution.
Self-healing bots for dynamic UI changes.
Integration:
40+ tools (Jira, Azure DevOps, Slack).
CI/CD pipelines (Jenkins, GitHub Actions).
Governance:
Role-based access, audit logs, and data encryption.
Deployment:
Cloud, on-prem, or hybrid (supports headless execution).
Incorporate AI-powered agents with semantic understanding and NLP capabilities.
Offer a low-code environment that supports testers with minimal scripting skills.
Provide self-healing automation to adapt to UI changes.
Focus on cross-platform compatibility (mobile, web, APIs).
Integrate with major CI/CD pipelines and test management tools.
Implement modular AI tools like agent builders for customizable automation.
Audience Interest: Questions focused on AI validation, data privacy, and integration (e.g., Jira, SAP).
Limitations: UiPath’s reliance on third-party LLMs (GPT, Claude) may raise concerns about data governance.
Q: What is agentic testing and can I use the agents today?
A: Yes, the agentic capability is in preview and can be used today. It enables autonomous test execution using AI-powered agents.
Q: Can UIPath test AI models and also use AI to test software?
A: Yes. UIPath tests both AI applications and uses AI to enhance testing processes, including semantic verification, natural language processing, and performance testing.
Q: Can the platform support natural language-based test case creation?
A: Yes. Users can generate and modify test cases using natural language prompts via Autopilot and Agent Builder.
Q: Does UIPath offer self-healing automation?
A: Yes. The platform includes self-healing agents that adapt test execution based on system or UI changes without requiring manual updates.
Q: Can agents be used to fine-tune AI models or LLMs?
A: Yes. Agents can generate test data, validate outcomes, and optionally assist in retraining models with human-in-the-loop validation.
Q: Are agent-generated test actions rule-based and configurable?
A: Yes. Agent behaviors can be fully customized using internal rules, prompts, and logic layers.
Q: Is the system capable of vector-based RAG (retrieval-augmented generation)?
A: Yes. It uses vector databases for context grounding in test case generation and AI verification.
Q: Will this replace manual testing?
A: Not entirely. It augments manual testers, enabling them to automate more effectively, but does not eliminate the need for human insight.
