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Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Free browser-based pseudocode editor and compiler with exam-board syntax modes, aimed at computer science students and teachers.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Open-source terminal AI pair programmer that edits code in your local git repo and auto-commits, working with most LLMs.
Open-source, self-hostable AI coding agent with autocomplete, in-IDE chat and autonomous task execution for teams needing data control.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦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
- ✦Syntax highlighting and error checking for pseudocode
- ✦Cloud-based project saving across devices
- ✦Built-in pseudocode compiler for instant execution
- ✦Toggleable syntax rules for AQA, OCR, CIE, Edexcel and IB
- ✦AI tutor and code-to-language converters (Pro tier)
- ✦Bulk institutional licensing for schools and universities
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Terminal-based AI pair programming
- ✦Edits code in your local git repo
- ✦Automatic git commits with messages
- ✦Codebase mapping for large projects
- ✦Works with cloud and local LLMs
- ✦Voice-to-code, image/web context, lint and test
- ✦Autonomous AI agent that plans and executes multi-step coding tasks
- ✦In-IDE chat for asking, editing, debugging and generating code
- ✦Real-time code autocompletion using retrieval-augmented generation
- ✦Repository search and analysis for context-aware execution
- ✦Integrations with GitHub, databases and CI/CD pipelines
- ✦Self-hosted/on-premise deployment option for data privacy
- ✦Support for choosing among different underlying LLMs
- →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
- →Students learning programming logic before writing real code
- →Teachers grading pseudocode assignments to exam-board specs
- →Exam preparation for computer science courses
- →Converting pseudocode into Python, C++ and other languages
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Building features and fixing bugs via AI in the terminal
- →Working on large existing codebases
- →Automating git commits
- →Using local LLMs for private coding
- →Developer teams wanting an in-IDE autonomous coding agent
- →Organizations requiring on-premise/self-hosted AI coding tools for data control
- →Individuals doing 'vibe coding' with minimal manual coding
- →Teams fine-tuning an AI assistant to their own codebase