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Self-hosted cloud development environments and AI-agent governance, letting enterprises run coding agents on their own infrastructure.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Data-annotation platform with AI-assisted labeling tools and team workflows for building ML training datasets.
No-code AI platform that builds full-stack apps, websites and agents from plain-language prompts with hosting built in.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦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)
- ✦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 with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦AI-assisted data annotation tools
- ✦Training-data platform (BasicAI Cloud)
- ✦Team and project management
- ✦Annotation services
- ✦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
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Standardize developer environments
- →Run AI coding agents securely on-prem
- →Enforce governance and compliance
- →Cut VDI costs
- →Speed up developer onboarding
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Labeling images and data for ML models
- →Managing annotation teams and projects
- →Producing training datasets at scale
- →Building internal tools and dashboards
- →Launching websites and landing pages
- →Creating customer portals and CRMs
- →Deploying AI agents that automate tasks