Private AI for Data Work
MLJAR Studio is your fully private AI Data Analyst and Machine Learning Engineer that runs 100% locally on your computer. Talk to your data in natural language, automatically build machine learning models, and generate actionable insights.No cloud. No data leaks. Just results.
Users & Companies
From research labs to fast-moving product teams, people rely on MLJAR to analyze data and ship insights.
Work With Your Own AI Data Analyst
MLJAR Studio includes an AI assistant that understands your data and helps you explore it.
Let AI Run Machine Learning Experiments
Building good machine learning models requires many experiments. MLJAR Studio can run these experiments for you.
AI Assistance Inside Your Notebook
When working in notebooks, the AI assistant helps you write and improve code.
Turn Your Analysis into Interactive Apps
With one click you can turn your notebook into a web application.
Why MLJAR Studio Is Different
Most AI tools require sending your data to the cloud. MLJAR Studio works differently. Everything runs on your machine, using real Python execution and fully reproducible notebooks.
Your data never leaves your computer.
Not a toy interface - a full data science workspace.
Every result can be reproduced from code.
Share results without relying on external services.
MLJAR tools have been used in a wide range of machine learning projects, including healthcare data analysis, financial modeling, manufacturing optimization, and many structured data problems.
MLJAR Studio is perfect for:
Move faster with AI assistance, visual exploration, and notebook-friendly workflows.
Iterate with reproducible pipelines, model comparisons, and transparent Python execution.
Keep projects local while maintaining auditability and reproducibility.
Use AI capabilities in a controlled environment without exposing data to external services.
MLJAR Studio helps you analyze data with AI, run machine learning workflows, and build reproducible notebook-based results on your own computer.
Runs locally • Supports local LLMs