Mito provides a Jupyter‑native spreadsheet interface that lets analysts edit data with Excel‑like formulas, pivots, and visualizations while automatically generating pandas code. An integrated AI assistant offers context‑aware code suggestions, error correction, and autocomplete, and the platform connects directly to databases and file sources, all running on the user’s own infrastructure for data privacy.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Data scientists and analysts often need to write extensive Python code to clean, transform, and visualize data, which slows down insight generation and requires programming expertise. Additionally, many organizations are concerned about data privacy when using cloud‑based AI tools for data manipulation.
Solution
Mito offers a Jupyter‑native spreadsheet interface that lets users edit data with familiar Excel‑like formulas, pivots, filtering, and visualizations while automatically generating the underlying pandas code. An integrated AI assistant (Jupyter Agent) can understand the notebook context, suggest transformations, fix errors, and autocomplete code, all running on the user’s own infrastructure. The platform supports direct connections to databases and file sources, enabling import/export of CSV, Excel, and remote data without manual scripting. Enterprise deployments can connect to private LLM providers and on‑prem AI models, ensuring that no data leaves the organization while still providing AI‑driven automation.
Target Audience
Primary users are data analysts, data scientists, and business intelligence professionals in enterprises who work in Jupyter notebooks and need faster, low‑code data preparation and visualization.
Features
- Spreadsheet UI embedded in Jupyter, Streamlit, and Dash that syncs with pandas dataframes
- Excel‑style formulas, pivot tables, sorting, filtering, and conditional formatting
- AI-powered Jupyter Agent for context‑aware code suggestions, error correction, and autocomplete
- One‑click chart wizard that generates Plotly visualizations as Python code
- Built‑in database connectors for importing data from SQL and NoSQL sources
- On‑prem AI integration allowing use of private LLMs (Azure, AWS, LiteLLM, etc.)
- Export of transformed data to CSV, XLSX, and direct dataframe updates
- Admin controls, telemetry toggle, and enterprise support features