Agent Assurance by TestMu AI Integrations

TestMu AI (Formerly LambdaTest) is an Agentic AI Quality Engineering platform that assures AI deployments across the enterprise and the real world. It runs agentic testing for web and mobile apps on 3,000+ browsers and 50,000+ real devices, and for chat, voice, IVR, video, and image agents. For test creation, KaneAI turns natural language prompts, PRDs and tickets into end-to-end tests that it plans, authors, runs and keeps up to date as the app changes. Kane CLI brings the same agent to the terminal, so developers, coding agents and CI pipelines can confirm that a browser flow really works. For teams shipping AI products, Agent Testing builds 60 to 100+ scenarios from PRDs, docs or Jira and measures chatbots, voice assistants and phone agents on hallucination, bias, tone and compliance, then gives a Green, Yellow or Red go-live verdict. Agent Assurance checks agents that take actions, such as coding and workflow agents, by grading the files, artifacts and tool calls they actually produced, and reports Pass, Fail or Unable to Verify. On the infrastructure side, Selenium, Playwright, Cypress and Appium suites run in parallel on the Automation Cloud, HyperExecute runs them up to 70% faster, App Automation supports Appium, Espresso and XCUITest on physical iOS and Android hardware, and Browser Cloud provides browsers built for AI agents. Performance Testing adds protocol-level JMeter load tests. SmartUI compares screenshots to flag visual regressions, the Accessibility Testing Agent audits apps against WCAG, ADA and EAA with TalkBack and VoiceOver on real devices, Test Manager keeps manual and automated cases together, and Test Insights spots flaky tests and explains failures with AI root cause analysis. The TestMu AI MCP Server lets AI clients pull test data. TestMu AI plugs into 120+ tools, from CI/CD servers to issue trackers and team chat, and is used by 3M+ users at 18,000+ enterprises, including Microsoft, OpenAI and Nvidia.

This groundbreaking AI-powered platform harnesses the power of advanced Large Language Models (LLMs) to revolutionize the way tests are created, debugged, and optimized. By utilizing natural language, it presents a unique approach to crafting comprehensive end-to-end tests. Users can easily generate and improve tests by inputting simple natural language commands, which enhances the testing process through intelligent automation. The platform’s smart test planner autonomously devises and executes test steps that align with overarching project goals. Furthermore, it supports multi-language code export, allowing for the conversion of automated tests into various major programming languages and frameworks. Users can translate their actions into natural language instructions, developing robust tests that align perfectly with their specifications. By expressing intricate conditions and assertions in everyday language, the platform simplifies the interaction, making it as easy as conversing with team members. When you communicate the same instructions to KaneAI, you will witness its impressive capability to automate your testing efforts efficiently. The platform enables the generation of thorough tests based only on high-level objectives, facilitating development across your entire technology stack and guaranteeing comprehensive test coverage for both web and mobile applications. With this innovative solution, the testing process transcends being a mere requirement and seamlessly integrates into your development workflow, ultimately enhancing productivity and efficiency. Embrace this transformation and watch your testing capabilities flourish.

Design drift, broken layouts and changed documents are hard to spot by eye across every page and device. SmartUI by TestMu AI takes over that check for QA engineers, front-end developers and design teams, comparing what users see against approved references. One dashboard covers several kinds of source. Websites and web apps are captured from automated tests or from a list of static URLs. Native app screens captured on real devices can be compared with their Figma frames, and Figma designs can also be checked against live web pages. PDFs are checked for text, layout, font and graphic differences. For component libraries, the Storybook CLI can capture only the stories a change affects and fail a CI job when its visual policy is broken. A/B testing lets one screenshot or PDF page keep up to 20 approved baseline variations, so each experiment variant has its own reference. Builds export to PDF, CSV or JSON, and the TestMu AI Tunnel reaches internal, development and staging environments. The SmartUI MCP server returns natural-language summaries of pixel, layout, DOM and perceptual differences. The open-source SmartUI Agent Skill lets Claude Code, Cursor and other coding agents add visual tests from one prompt, and KaneAI can include a visual comparison step in its test cases and schedule the runs. When something breaks, Smart RCA ranks changes from critical to low severity, and the diff and fix can go to Jira or Slack in one click. Pricing is volume-based by screenshot count, with unlimited user seats. The free tier is a one-time allowance of 2,000 screenshots, and paid plans start at $199 a month for 15,000 screenshots, billed annually. TestMu AI (Formerly LambdaTest) is an Agentic AI Quality Engineering platform that assures AI deployments across the enterprise and the real world. It runs agentic testing for web and mobile apps on 3,000+ browsers and 50,000+ real devices, and for chat, voice, IVR, video, and image agents.

TestMu AI presents an all-encompassing platform dedicated to assessing the quality of AI agents, tailored for teams focused on building conversational and multimodal interfaces that interact with customers effectively. This platform is capable of evaluating a wide range of agents, including those that function through chat, voice, and even video and images, by generating scenarios based on a multitude of sources such as product specifications, documentation, and tools like Jira and Confluence, and subsequently simulating interactions with the chosen agent. A specialized team of over 15 evaluators meticulously examines the agents' responses, concentrating on crucial attributes such as accuracy, hallucination, bias, completeness, contextual understanding, and tone; for chat and voice evaluations, nine distinct quality metrics are utilized, while assessments of phone calls incorporate more than 30 metrics. The comprehensive reports generated offer in-depth insights at the conversation level, along with a readiness rating categorized as Green, Yellow, or Red, which empowers QA, AI/ML, product, and compliance teams to identify potential issues before launch and to benchmark agent performance across various iterations. Moreover, teams can take advantage of the ability to schedule tests and use a command-line interface for consistent execution of tests, facilitating integration within continuous integration pipelines, thus improving their overall testing efficiency. This structured methodology not only contributes to enhancing the quality of AI agents significantly but also cultivates increased confidence among stakeholders regarding their launch and utilization. As a result, organizations can leverage these insights to make informed decisions about their AI deployments.

Introducing an advanced browser designed specifically for the creation, evaluation, and troubleshooting of mobile websites. This tool enables users to examine their sites through a variety of pre-loaded mobile device viewports. LT Browser is a versatile mobile browser that lets you experience your website as it would appear on both iOS and Android platforms. If your preferred device is not available, LT Browser offers the flexibility to design your own custom viewport and save it for future access. You can generate new configurations for mobile, tablet, or desktop devices, allowing for comprehensive testing of your website. Additionally, it allows you to assess screen resolutions across various devices, streamlining the process of mobile website testing without the need to switch between multiple gadgets. With LT Browser, you have the unique capability to test on two devices at once, facilitating simultaneous evaluations of tablets and desktops in varying resolutions. This tool also includes integrated DevTools that empower you to test responsiveness across multiple devices concurrently. You can seamlessly verify your website's performance on different resolutions while utilizing distinct DevTools for each test, ensuring a thorough and efficient testing experience. This combination of features makes LT Browser an essential asset for developers focused on optimizing mobile web experiences.

Kane CLI is an advanced testing tool for AI that operates within terminal environments, created by TestMu AI, which was formerly known as LambdaTest. This adaptable software can be used across various settings such as terminals, IDEs, or CI pipelines, and it works seamlessly with AI coding agents like Claude Code, Codex CLI, and Gemini CLI. To perform a basic operation, the user simply needs to log into the system, add a laptop to their cart, apply the discount code SAVE10, and review the final total. Through the capabilities of Kane CLI, a genuine Chrome browser executes these tasks step by step, yielding a straightforward pass or fail outcome along with a link that serves as verifiable evidence. The tool obviates the necessity for selectors or boilerplate code, which means setting up a test framework beforehand is not required. It is specifically designed to cater to two primary audiences: developers, QA engineers, product managers, and casual coders who can check a feature before a pull request, during the QA phase, and right before deployment. Conversely, AI coding agents utilize Kane CLI as a crucial verification resource; while they can generate features from prompts, they cannot verify their functionality in a real browser. Therefore, Kane CLI fulfills this essential validation role and can be installed with just one command, highlighting its user-friendly and efficient nature. This dual functionality not only fosters collaboration among team members but also significantly optimizes the testing process across different groups. Additionally, its simplicity empowers users to integrate testing into their workflows without extensive technical knowledge.