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One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
Testing and evaluation platform for voice and chat AI agents, running simulations, production monitoring and human QA review.
No public pricing
Free trial available
No public pricing
Free trial available
Free trial available
- ✦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)
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦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
- ✦AI-summarized commit and PR reports
- ✦Daily and weekly scheduled digests
- ✦Slack and email delivery
- ✦One-click OAuth or webhook setup
- ✦GitHub, GitLab and Bitbucket support
- ✦Templates for standups and reports
- ✦Voice agent simulation at scale
- ✦Production call monitoring and evals
- ✦Human QA review queues
- ✦Regression testing across changes
- ✦Vendor bake-off comparisons
- ✦API, CLI and MCP interfaces
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity
- →Pressure-testing voice agents before launch
- →Catching quality drift in production
- →Comparing voice AI vendors objectively