AI Test Manager vs OpenTest.AI
AI Test Manager
github.comOpenTest.AI
opentest.aiSide by side
| Figure | AI Test Manager | OpenTest.AI |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | — |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · AI Test Case Generators | 7.8 (#11) | 7.8 (#12) |
Plans
In their own words
AI Test Manager
AI Test Manager is a free Windows desktop application that turns a one-line requirement or scenario into structured use cases and test cases with AI. Users enter a scenario, generate results, then copy, export, or reuse them; generated cases can be exported to Excel. The application supports local inference through an Ollama endpoint, or users can provide a token for a paid API endpoint. Its repository describes the tool as requiring no login or coding and says it is MIT licensed for personal and commercial use. Setup consists of downloading and extracting the ZIP, opening AI_TestManagement.exe, and entering an AI endpoint and model name. The maker presents it for QA and development workflows. It is described as a Windows desktop tool, with local or cloud AI models in the plan details. The Free plan costs nothing. The repository owner identifies the maker as Sooraj Ramachandran, whose profile lists NYC.
OpenTest.AI
OpenTest.AI is a self-hosted, open-source project for local-first AI quality checks and portable JSON testing formats. Its six skills include automatic bug fixing, deep quality scans, risk analysis, statistical confidence analysis, smart comparisons, and metrics. The skills run locally without an API key, cloud call, or account, and integrate with clients such as Claude Code, Cursor, Codex CLI, GitHub Copilot Chat, Aider, and Continue.dev. jank_deep scans 12 quality dimensions, while jank_risk follows code blast radius, GenAI smells, user frustration, and business risk. jank_confidence uses test-coverage statistics and estimates the cost and time to close gaps. jank_diff compares APIs, documents, or local files while ignoring timestamps, dynamic IDs, and generated metadata noise. The project analyzes screenshots, network and console logs, and DOM or accessibility trees through 33+ AI testing profiles. It supports bug detection, persona feedback, and prioritized test-case generation. Test cases can be replayed by Playwright, Selenium, Cypress, or a human. The MIT plan is free forever.