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Execution-fabric infrastructure that splits AI/compute workloads into units and packs GPUs to cut cost and raise utilization.
Open-source, encrypted web terminal sharing tool letting people collaborate live on one command line via a browser link.
Documentation and knowledge platform that keeps developer docs self-updating and queryable by AI agents.
Serverless cloud browser API with persistent sessions, built-in stealth and proxies, for AI agents, automation and scraping.
Headless, open-source rich-text editor framework with paid add-ons for collaboration, comments, AI editing agents and document conversion.
No public pricing
No public pricing
Free trial available
Free trial available
Free trial available
- ✦Decomposes workloads into small routable units
- ✦Packs GPUs/CPUs to raise utilization
- ✦Works with Kubernetes, SLURM, CUDA and ROCm
- ✦Runs on cloud, on-prem and edge
- ✦Sits beneath existing orchestration with no rewrite
- ✦One-command installation and session sharing via link
- ✦End-to-end encryption so the server cannot read terminal data
- ✦Multiplayer infinite canvas for arranging multiple terminals
- ✦Live cursors and chat for real-time collaboration
- ✦Cross-platform CLI for macOS, Linux and Windows
- ✦Distributed mesh networking for low-latency global connections
- ✦Self-updating documentation
- ✦Web-based documentation editor
- ✦Custom domain hosting
- ✦Built-in search and API playground
- ✦MCP server for agent access
- ✦Authentication and access controls
- ✦Serverless cloud Chromium browsers
- ✦Persistent logged-in sessions
- ✦Built-in stealth / anti-detect fingerprinting
- ✦Residential & datacenter proxies in 150+ countries
- ✦Playwright/Puppeteer WebSocket connection
- ✦Headful mode for live inspection
- ✦Headless, extensible core editor with 100+ extensions
- ✦Real-time collaborative editing with live cursors
- ✦Inline and document comments
- ✦DOCX, ODT and Markdown import/export
- ✦AI Toolkit for building document-editing AI agents
- ✦Prebuilt UI components and editor templates
- →Increasing GPU cluster utilization
- →Cutting AI/compute infrastructure cost
- →Speeding up training and inference workloads
- →Getting more from existing hardware without migration
- →Pair debugging a remote server with a teammate
- →Teaching command-line skills over a shared live session
- →Sharing a CI/CD pipeline terminal for troubleshooting on GitHub Actions
- →Providing temporary cloud access without exposing SSH credentials
- →Publish and maintain developer documentation
- →Expose docs to AI agents via MCP
- →Host a branded docs site on a custom domain
- →Give teams a collaborative doc editor
- →Running AI browser agents
- →Web scraping at scale
- →Automating logged-in workflows
- →Debugging automation in live sessions
- →Building a custom rich-text editor for a SaaS product
- →Adding real-time collaboration to a document app
- →Letting an AI agent edit documents with tracked changes
- →Importing or exporting Word or Markdown content in-app
