4.5 out of 5 stars
(131 Ratings)
Virtuoso QA is a secure, agentic test automation platform for any browser-based application. Touchstone, our agentic assurance layer, turns your business requirements into tests, then runs, fixes and maintains them as your application changes. More than thirty specialised agents author, generate, triage and self-heal your functional and end-to-end tests, while a deterministic engine executes every run and your team approves every decision that matters. Every release comes with evidence of what was tested, what changed and who approved it. Release Insights shows execution risk and requirement coverage across every journey, and teams can export an Evidence Report in minutes rather than assembling one over weeks. That makes the platform a natural fit for regulated industries like financial services, insurance, healthcare, the public sector and more.
The mission is to set the standard of proof for software releases. AI generates software. Virtuoso QA generates the evidence to trust it.
Learn more about Virtuoso QA
4.6 out of 5 stars
(608 Ratings)
Retool is a modern AI-native application development platform designed to help teams build internal software quickly and efficiently. It enables users to create agents, workflows, dashboards, and full-stack apps using natural language prompts and visual tools. Retool connects directly to databases, APIs, vector stores, and AI models to ensure applications work seamlessly with existing systems. The platform allows teams to transform raw data into actionable tools such as dashboards, admin panels, and monitoring systems. With drag-and-drop UI building, code-level customization, and AI-assisted generation, Retool supports multiple development styles. Built-in workflows automate complex processes while maintaining auditability and security. Retool fits naturally into standard engineering stacks with support for CI/CD and version control. Enterprise-grade permissions and hosting options ensure sensitive data stays protected. Used by thousands of companies worldwide, Retool helps teams ship AI-powered software faster. It bridges the gap between idea and production with speed and control.
Learn more about Retool
Kandev
Kandev serves as an open-source development platform designed to facilitate the coordination of AI coding agents alongside software tasks. This workspace unifies various functionalities, including task planning, agent sessions, repository activities, code modifications, and reviews, allowing developers to execute agents simultaneously, manage workflows with Kanban boards, examine differences in code, and assess changes prior to initiating or merging pull requests. Additionally, users can integrate their preferred coding-agent CLIs or ACP agents and interact with repositories via platforms like GitHub, GitLab, Azure DevOps, Jira, Linear, and Sentry. Kandev can be operated locally or on user-managed infrastructure, offering deployment options such as CLI, desktop, Docker, and service models. Executors available within the platform encompass local environments, isolated worktrees, Docker, SSH, and remote setups, while task coordination is facilitated through MCP, webhooks, and automated scheduling. Tailored for software developers and engineering teams, Kandev aims to create a collaborative workspace that enhances agent-assisted coding and streamlines the code review process. By centralizing these tools and processes, Kandev promotes efficiency and productivity within development teams.
Learn more about Kandev
ML.ai
Ml.ai serves as an AI coding assistant that follows your code wherever it may be. You can utilize it within environments like VS Code and Cursor, through its dedicated desktop application without the need for an IDE, by accessing it via the terminal, or as a pull request reviewer that evaluates each submission. Every interface operates using the same underlying technology, maintaining consistent settings and a unified memory of your repository.
Unlike many coding agents that rely on a single costly frontier model for every action, Ml.ai assigns specific tasks to specialized agents, selecting the most cost-effective model that meets your desired quality standards, often resulting in a reduction of model expenses by 30 to 45% for similar tasks. Its Explore feature reads and interprets the codebase, while Architect and Plan organize the project files, sequence tasks, and assess potential trade-offs. Only the General agent has the authority to make code alterations, ensuring that every change or command is subject to your explicit permission to Allow or Deny. The PR Reviewer not only provides a summary of each pull request but also adds detailed comments at the line level and executes builds and tests before suggesting either approval or requests for changes, without the ability to merge independently.
Additionally, Ml.ai offers reusable skills, supports background operations, and includes MCP server functionality, enhancing its overall utility.
Learn more about ML.ai
