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GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
AI agent-based end-to-end testing platform for SaaS teams that runs exploratory and PR-triggered tests without maintaining test scripts.
AI-based test automation tool that lets QA teams and non-technical staff write and maintain end-to-end tests in plain English.
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
- ✦Contribution and work-quality analytics
- ✦Automated, AI-powered performance reviews
- ✦Retrospective insights
- ✦Operational bottleneck alerts
- ✦Gamification with XP, levels and leaderboards
- ✦Uses Git metadata without accessing source code
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦AI agents that visually explore and test UI like a real user
- ✦Automatic PR-triggered test runs via GitHub/Vercel preview integration
- ✦Self-healing tests that adapt to UI and workflow changes
- ✦Mobile web, iOS, and Android app testing support
- ✦Detailed debugging with screenshots, logs, and failure reasoning
- ✦Cloud-native execution with no source-code access required
- ✦Plain-English test authoring and execution
- ✦Generative AI self-healing to reduce test maintenance
- ✦Coverage across web, mobile, desktop, API, and mainframe apps
- ✦Built-in support for email, SMS, phone calls, and 2FA testing
- ✦Test recorder for faster initial test creation
- ✦Import of existing manual test cases
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Engineering teams wanting regression testing without maintaining scripts
- →SaaS companies needing continuous QA feedback on every pull request
- →Teams replacing manual QA hours with automated agent-driven testing
- →Reducing test-maintenance workload for QA teams
- →Letting business analysts write automated tests without coding
- →Running cross-browser and cross-platform tests in one suite
- →Automating regression testing for CRM and ERP systems