Show HN: Mljar Studio – local AI data analyst that saves analysis as notebooks
Source: Hacker News
Overview
I’ve been working on mljar‑supervised (open‑source AutoML for tabular data) for a few years. Recently I built a desktop app around it called MLJAR Studio.
The idea is simple: you talk to your data in natural language, the AI generates Python code, executes it locally, and the whole conversation becomes a reproducible notebook (*.ipynb). Instead of just chatting with data, you end up with something you can inspect, modify, and rerun.
What MLJAR Studio Does
- Sets up a local Python environment automatically; runs on macOS, Windows, and Linux
- Installs missing packages during the conversation
- Built‑in AutoML for tabular data (classification, regression, multiclass)
- Works with standard Python libraries (pandas, matplotlib, etc.)
- Supports any data file: CSV, Excel, Stata, Parquet …
- Connects to PostgreSQL, MySQL, SQL Server, Snowflake, Databricks, and Supabase
AI Backend Options
- Use Ollama locally (zero data egress)
- Bring your own OpenAI key
- Use the MLJAR AI add‑on
Motivation
I built this because I wanted something between Jupyter Notebook (flexible but manual) and AI tools that generate code but don’t preserve the workflow. Most tools I tried either hide too much or don’t give reproducible results and are cloud‑based.
Demos
- 60‑second demo:
- Full 3‑minute analysis:
Pricing
- $199 one‑time with a 7‑day trial
Call for Feedback
Curious if this is useful for others doing real data work, or if I’m solving my own problem here. Happy to answer questions.