PlotStudio AI: Agentic data analysis for researchers

Hey Product Hunt! I’m Aymen, founder of AR5Labs and creator of PlotStudio AI 👋

PlotStudio came from a pretty simple frustration: I never really liked the way most AI data analysis tools were designed.

I worked as a data scientist for a flight simulator company. A lot of the job was investigative: exploring datasets, testing hypotheses, following leads, and figuring out whether something was actually a signal or just noise.

When AI coding agents started getting good, they felt like a much better abstraction for data analysis to me than chatting with a tool that generates a chart or answers one question at a time.

That was the foundation I wanted.

I started experimenting with deeper research-style agent workflows for data analysis, and over time that evolved into PlotStudio: the data analysis environment I wished I had when I was working as a data scientist.

The original goal was simple: I wanted to be able to give an agent my data and a broad question, walk away, and come back to actual signal instead of spending hours chasing noise.

As people started using PlotStudio, researchers became some of our most engaged users. That pushed the product much further toward serious statistical and research workflows.

Today, PlotStudio is an AI-powered workspace built around agents designed for statistical analysis, with our own semantic layer to help them reason about datasets and analytical workflows. Agents can inspect your data, plan analyses, write and execute Python or R, create visualizations, validate findings, and turn the work into structured, publication-ready outputs.

Your datasets, analyses, results, and context also live together in a persistent workspace, so the system gets more context as your project evolves rather than starting from scratch with every question.

Users can also adapt PlotStudio to niche domains and specialized analytical workflows.

The philosophy behind it is still the same one I started with: give the AI more of the investigative work, spend less time chasing noise, and spend more time thinking about the signal that actually matters.

I’d love to hear about the data analysis workflows you still don’t trust AI to handle.