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GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
Self-hosted cloud development environments and AI-agent governance, letting enterprises run coding agents on their own infrastructure.
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
No public pricing
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No public pricing
- ✦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)
- ✦BYOK access to 15+ model providers
- ✦Agentic planning-then-build mode
- ✦AI autocomplete
- ✦MCP connections to external systems
- ✦Custom rules and live context tracking
- ✦Local models via Ollama/LM Studio
- ✦VS Code and JetBrains plugins
- ✦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
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- →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
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →Standardize developer environments
- →Run AI coding agents securely on-prem
- →Enforce governance and compliance
- →Cut VDI costs
- →Speed up developer onboarding
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools