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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.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
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- ✦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
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦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
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- →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
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign