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Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Topic and question research tool that aggregates search, social, and SEO data to generate blog and content ideas.
An AI whiteboard for content creators that pulls in your channels and research to find ideas, write scripts and draft posts in your voice.
No public pricing
Free trial available
No public pricing
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
- ✦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)
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Topic Model for cross-web content research
- ✦Social Model covering Reddit, Twitter, TikTok, Instagram and more
- ✦Question Finder for audience-question discovery
- ✦Search volume, trends, sentiment and CPC data
- ✦Saved lists and shareable workspaces
- ✦Multi-language and multi-country reports
- ✦CSV export
- ✦AI whiteboard workspace for content
- ✦Connects YouTube, Instagram, competitors and research
- ✦AI idea discovery from your channels
- ✦AI script and post generation in your voice
- ✦Consolidates multiple content tools
- →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
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Content marketers finding blog topic ideas
- →Social media managers tracking trending discussions
- →SEO teams researching keyword search volume and CPC
- →YouTube/podcast creators finding audience questions
- →Finding content ideas that perform
- →Writing video scripts faster
- →Drafting social posts in a consistent voice