TGenAI utilizes advanced AI and large language models to transform the process of creating test cases. By analyzing web pages, it extracts relevant components and automatically generates comprehensive test scenarios. This not only reduces manual input but also minimizes errors, allowing teams to focus on higher-level testing strategies. Whether for user interfaces, APIs, or other web functionalities, TGenAI helps ensure that your applications are thoroughly validated, enabling faster releases with improved quality.

ToolFuzz provides a comprehensive fuzz testing framework specifically tailored for tool-using AI agents. It systematically generates randomized tool invocation sequences, malformed API inputs, and unexpected parameter combinations to stress-test the agent’s tool-calling modules. Users can define custom fuzz strategies using a modular plugin interface, integrate third-party tools or APIs, and adjust mutation rules to target specific failure modes. The framework collects execution traces, measures code coverage for each component, and highlights unhandled exceptions or logic flaws. With built-in result aggregation and reporting, ToolFuzz accelerates the identification of edge cases, regression issues, and security vulnerabilities, ultimately strengthening the robustness and reliability of AI-driven workflows.

Webo.AI provides a comprehensive, AI-powered test automation platform designed to revolutionize the quality assurance process. Leveraging Artificial Intelligence, Webo.AI enables automated test case generation, execution, and defect detection. Its user-friendly interface ensures that both technical and non-technical users can swiftly adopt and benefit from reduced testing time, minimized defects, and overall improved software quality. With features aimed at increasing efficiency and accuracy in software testing, Webo.AI is a valuable asset for any development team.

Anti-Agent-Agent provides a programmable framework to generate both adversarial and defensive AI agents for conversational models. It automates prompt crafting, scenario simulation, and vulnerability scanning, producing detailed security reports and metrics. The toolkit supports integration with popular LLM providers like OpenAI and local model runtimes. Developers can define custom prompt templates, control agent roles, and schedule periodic tests. The framework logs each interaction, highlights potential weaknesses, and recommends remediation steps to strengthen AI agent defenses, offering an end-to-end solution for adversarial testing and resilience evaluation in chatbot and virtual assistant deployments.