What is Mito AI?

Mito is a Jupyter extension that converts Excel spreadsheets into Python code, allowing analysts to automate reporting without manual scripting. It offers a spreadsheet interface, a point‑and‑click chart wizard, and automatic error correction to streamline exploratory data analysis and feature engineering.

Machine‑learning engineers can run low‑code SQL queries and connect to databases directly from notebooks, while a built‑in Jupyter agent updates notebook content based on AI suggestions. The tool operates entirely on existing infrastructure, supports multiple LLM providers—including Azure, AWS, OpenAI, Anthropic, Gemini, and Qwen—ensuring user data remains within the organization.

Mito integrates with standard Jupyter extensions and can convert notebooks into Streamlit applications for team sharing. Enterprise installations add administrative controls, database and LLM integrations, and training resources for scalable Python adoption.

Mito AI pricing Paid

$4200

$5000

$6100

Verify on the official pricing page.

View plans

Mito AI user reviews

Based on 1 review, 100.0% of users recommend Mito AI, rated highly for ease of use.

recommend

don't

1 review

Liked for

Worth the price 1 of 1

Easy to use 1 of 1

Would you recommend Mito AI?

Recommend this tool?

Mito AI's key features

Jupyter extension for notebook automation
Runs locally on your infrastructure
Supports multiple LLM providers
Low‑code SQL database integration
Automates Excel report creation
Auto‑error correction in code
Builds Streamlit apps from notebooks

Mito AI use cases

Convert a multi‑sheet Excel workbook containing sales and inventory data into a ready‑to‑share Jupyter notebook using Mito’s spreadsheet UI and point‑and‑click chart wizard, then export it as a Streamlit app for interactive dashboards accessible to non‑technical stakeholders
Use Mito’s low‑code SQL interface to draft, test, and run complex queries against your corporate data warehouse directly from a familiar spreadsheet grid, enabling data scientists to prototype analytics pipelines and save the notebook for version control
Leverage Mito’s AI‑assisted notebook updates to automatically correct errors, refactor legacy data‑cleaning code, and add explanatory comments, so developers can maintain high‑quality, reproducible notebooks with minimal manual effort