Built around the scientific workflow
A connected research record
The aim is to make experimental decisions easier to inspect and reproduce. Keep the research question, factor definitions, original observations, methods, and resulting evidence connected throughout a study.
For teams doing applied science
Designed for industrial R&D teams, formulation developers, materials and process researchers, and applied laboratories working with controlled experiments and measured responses.
Evidence with its context
Compare predictive models against a transparent baseline and evaluate on held-out observations. Keep assumptions, uncertainty, and the distinction between measurements and model estimates visible alongside the results.
Available in the current workspace
Create project and experiment records, import and inspect CSV datasets, run Python statistics and regression comparisons, explore response surfaces, propose supported continuous-factor experiments, and export reproducible reports.
Research is a team effort
Bring project and experiment records into a shared workspace. Request a review, discuss a result, record the reviewer’s decision, and preserve the history behind the next experiment.
The sample study uses synthetic observations so you can inspect the workflow and its methods. Current capabilities, scientific limitations, and deployment boundaries are documented in the Technical Documentation.