TestDino is a cloud-based Playwright test observability platform that records CI runs, detects flaky tests, and provides centralized debugging and analytics. It streams live results during test execution and makes failures and fix workflows queryable by both human teams and AI agents via MCP. The platform integrates with tools like GitHub, Jira, and Slack to streamline the entire testing workflow.
Funding
Funding not disclosed
Founders
Product
Problem
Teams running Playwright test suites in CI often lack visibility into what is actually passing or failing in real time, and they struggle to identify which tests are flaky and why. This forces engineers to spend significant time sifting through logs and traces to debug failures, slowing down development cycles and eroding trust in the test suite.
Solution
TestDino is a cloud-based companion for Playwright that records CI test runs and provides a centralized platform for debugging, flake detection, and analytics. It streams results live as tests execute, giving teams immediate insight into test health, and automatically classifies each test with a stability percentage and root cause category such as timing, environment, or network. The platform stores full traces, screenshots, and videos, and makes all data queryable and actionable for both human teams and AI agents through an MCP server and API. By integrating with CI/CD pipelines, issue trackers, and communication tools, TestDino ensures that failures are automatically surfaced with full context, enabling faster fixes and reducing time spent on false failures.
Target Audience
Primary customers are software engineering and QA teams using Playwright for end-to-end testing, particularly those running tests in CI environments who need better visibility, flake management, and AI-assisted debugging workflows.
Features
- Real-time streaming of test results with live worker status and pass/fail counts during CI runs
- Automatic flaky test detection with stability percentages and root cause categorization (timing, environment, network, assertion, or other)
- MCP server that allows AI agents to query test results, debug failures, and manage test cases directly from IDEs
- Pre-built integrations with GitHub, GitLab, Azure DevOps, Jira, Linear, Asana, Slack, and monday.com for automated summaries, issue creation, and alerts
- Native CI/CD plugins including a GitHub Action, CircleCI Orb, and TeamCity plugin for one-step report uploads
- Trace viewer with screenshots and videos for in-depth debugging of failed tests