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Open-source AI coding agent for VS Code, JetBrains, CLI and cloud, with 500+ models at zero inference markup and BYOK.
AI social-listening and customer-feedback platform that tracks brand mentions, creators, and sentiment across video-first social platforms.
Spreadsheet-style Python data tool inside Jupyter that generates code via AI so analysts and data scientists can skip hand-coding.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
Free trial available
No public pricing
No public pricing
No public pricing
- ✦500+ AI models at zero inference markup
- ✦Bring-your-own-keys and local model support
- ✦MIT-licensed, fully open source
- ✦Works in VS Code, JetBrains, CLI and cloud
- ✦Agent modes (Code, Architect)
- ✦Parallel isolated worktrees
- ✦Slack code reviewer and gateway
- ✦Access to a verified and engaged participant pool
- ✦Self-serve platform for easy task setup and launch
- ✦Tools for AI training and evaluation
- ✦Fair compensation for participants
- ✦Audience checker
- ✦Cross-platform social listening including video (TikTok, Reels, Shorts)
- ✦Competitive analysis of rival brands' content and creators
- ✦Speech-to-text and AI vision analysis of video content
- ✦Plain-language query interface for filtering data
- ✦Creator discovery and campaign tracking
- ✦Centralized customer feedback intake with AI tagging and sentiment
- ✦MCP connector for using data inside Claude/ChatGPT workflows
- ✦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
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
- →Writing and refactoring production code with AI
- →Planning features before implementation
- →Running agents across multiple IDEs and the CLI
- →Academic research
- →AI training and evaluation
- →Market research
- →User research & testing
- →Data annotation
- →Training & alignment
- →Evaluation & safety
- →Consumer brands monitoring sentiment and share of voice on social video
- →Marketing teams finding and vetting influencer partners
- →CX teams unifying feedback from tickets, chat, surveys and reviews
- →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
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app