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Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
No-code AI platform that builds full-stack apps, websites and agents from plain-language prompts with hosting built in.
Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦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)
- ✦Prompt-to-app full-stack generation
- ✦Built-in backend, database and auth
- ✦One-click integrations (Slack, Notion, HubSpot, etc.)
- ✦Instant hosting and custom domains
- ✦Superagents for automated workflows
- ✦GitHub sync and code export
- ✦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
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →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
- →Building internal tools and dashboards
- →Launching websites and landing pages
- →Creating customer portals and CRMs
- →Deploying AI agents that automate tasks
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity
