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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Full-stack AI cloud offering GPU compute, inference, fine-tuning and sovereign data centers for large-scale AI and HPC workloads.
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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)
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦On-demand GPU and CPU compute
- ✦Autoscaling inference endpoints
- ✦Serverless fine-tuning pipelines
- ✦Managed Kubernetes and Slurm
- ✦AI-optimized storage and RDMA networking
- ✦Sovereign, sustainable data centers
- ✦Fleet operations and observability
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Large-scale model training and fine-tuning
- →Deploying inference at scale
- →Running HPC and GPU workloads
- →Sovereign or compliant AI infrastructure