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AI interview copilot delivering real-time answer suggestions and live transcription across video, phone and coding interviews.
Spreadsheet-style Python data tool inside Jupyter that generates code via AI so analysts and data scientists can skip hand-coding.
A fast, keyboard-driven Mac/Windows launcher with an extension store and built-in AI commands for power users who live in shortcuts.
Local desktop app that assembles code-context prompts for LLMs, with API integrations, token tracking, and prompt saving.
No public pricing
No public pricing
Free trial available
- ✦Real-time answer suggestions
- ✦Live interview transcription
- ✦STAR and bullet response formats
- ✦Chrome extension for online assessments
- ✦AI interview prep and mock interviews
- ✦Multiple AI models (GPT, Claude, Gemini)
- ✦Spreadsheet interface inside Jupyter notebooks
- ✦AI-generated Python code from spreadsheet actions
- ✦Runs on customer infrastructure (no data sent to Mito)
- ✦Bring-your-own LLM API keys
- ✦Excel-to-Python conversion
- ✦Compatible with existing Jupyter extensions
- ✦Extendable command-bar launcher for macOS and beta Windows support
- ✦Thousands of third-party extensions from a public store
- ✦Built-in AI chat and custom AI command automation
- ✦Clipboard history, window management, and calculator utilities
- ✦Text snippets and quicklinks for repetitive actions
- ✦Hotkeys and aliases for common apps and commands
- ✦Team plan for sharing snippets, quicklinks, and extensions
- ✦Source-code context and prompt management
- ✦Custom and formatting instructions
- ✦BYOK API integrations (OpenAI, Claude, Gemini, etc.)
- ✦Token-limit tracking
- ✦Code-edit feature with visual diffs and backups
- ✦Local, offline prompt generation
- →Getting live help during interviews
- →Answering online coding assessments
- →Practising with AI-generated questions
- →Handling phone and video interviews
- →Analysts automating Excel-style reports without hand-writing code
- →Data scientists speeding up exploratory data analysis
- →ML engineers iterating on feature engineering in notebooks
- →Enterprises needing private, self-hosted AI coding assistance
- →Launching apps and running quick commands without leaving the keyboard
- →Automating repetitive text and file tasks with snippets and quicklinks
- →Getting AI answers or writing help without switching apps
- →Sharing productivity tooling and extensions across a team
- →Building context-rich prompts for AI coding
- →Comparing model outputs on the same task
- →Reusing saved prompts across tech stacks
- →Keeping code private during prompt creation