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Self-hosted cloud development environments and AI-agent governance, letting enterprises run coding agents on their own infrastructure.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Satellite data analytics provider turning imagery into AI-driven insights for agriculture, forestry and infrastructure.
Desktop workspace letting multiple AI coding agents (Claude Code, Codex, Cursor) collaborate on shared context and specs.
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No public pricing
No public pricing
No public pricing
- ✦Self-hosted workspaces with desktop and web IDEs
- ✦Coder Agents run coding agents on isolated infrastructure
- ✦AI Governance gateway for LLM usage control
- ✦SSO (OpenID Connect) and role/group sync
- ✦Audit logging and resource quotas
- ✦Multi-organization access controls
- ✦High availability and workspace proxies
- ✦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
- ✦LandViewer imagery search and analysis
- ✦Crop Monitoring for precision agriculture
- ✦EOS RayVision analytical reports
- ✦Crop classification and yield prediction
- ✦Infrastructure and change monitoring
- ✦Deforestation and damage mapping
- ✦EOSDA API and 20+ satellite data sources
- ✦Runs multiple coding agents (Claude Code, Codex, OpenCode, Cursor) in one workspace
- ✦Bring-your-own-subscription model for existing agent accounts
- ✦Agent-to-agent communication for questions, reviews and handoffs
- ✦Shared filesystem, decision history and specs per task
- ✦Mid-chat model switching without losing context
- ✦macOS desktop app
- →Standardize developer environments
- →Run AI coding agents securely on-prem
- →Enforce governance and compliance
- →Cut VDI costs
- →Speed up developer onboarding
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Monitoring crop health and predicting yields
- →Tracking infrastructure and construction
- →Disaster damage and deforestation mapping
- →Maritime and border surveillance
- →Developers coordinating multiple AI coding agents on the same project
- →Teams collaborating around shared agent context and specs
- →Switching between different LLMs mid-task without losing history
- →Reviewing and handing off in-progress coding work between agents