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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Enterprise AI agent platform for building, deploying, and governing no-code agents across company knowledge and workflows.
Spreadsheet-style Python data tool inside Jupyter that generates code via AI so analysts and data scientists can skip hand-coding.
No public pricing
No public pricing
Free trial available
No public pricing
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦Natural language to SQL conversion
- ✦No-code visual agent builder
- ✦Company knowledge search across docs and wikis
- ✦Scheduled and recurring agent automations
- ✦Model-agnostic access to major AI models
- ✦Browser extension integration with 30,000+ apps
- ✦Data analysis of spreadsheets and reports
- ✦Enterprise SSO/SCIM/SAML and dedicated deployment
- ✦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
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Generating SQL queries from text descriptions.
- →Automating recurring reports and workflow tasks
- →Searching internal company knowledge with AI agents
- →Deploying AI copilots for sales, support, or legal teams
- →Running enterprise AI with strict data governance requirements
- →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