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Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
An on-device developer memory tool that auto-captures code, docs and context across apps so engineers can search and reuse it later.
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
- ✦Natural-language to Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
- ✦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
- ✦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
- ✦Automatic capture of code, docs and context across apps
- ✦Long-term memory engine for time-based search of past work
- ✦One-click save, search and AI-tagging of code snippets
- ✦Local, on-device processing with optional cloud sync
- ✦Plugin support for browsers and IDEs like VS Code
- ✦MCP integration with external LLMs for contextual answers
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags
- →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
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →Recalling code snippets and context from past coding sessions
- →Feeding accurate personal context into AI coding assistants
- →Keeping research notes and links without manual bookmarking
- →Preserving shared context across team collaboration tools