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Braven connects to the way hardware R&D teams already work — folders full of measurement files, Python scripts, OneDrive syncs — and turns that into a structured, searchable record of every experiment your team has run. There are exactly two ways data gets into Braven, and they meet in the same place:

Folder Watcher

Point a desktop agent (or OneDrive) at a folder your instrument already writes to. Every new subfolder becomes an Experiment automatically — no code required.

Python SDK

Log experiments directly from your own analysis scripts, wandb-style: braven.init(), config(), summary(), upload().
Once data is in, two things act on it:

Pipelines

A small Python script that runs automatically against every new experiment’s files and writes back Config, Summary, Series, and Figures.

Analysis & Reports

Combine series and summaries across experiments to compare runs, then save the arrangement or share it as a Report.

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Where to start

1

Learn the vocabulary

Five minutes with the Glossary — Company, Project, Experiment, Run, Pipeline, Device — will make everything else click faster.
2

Get set up

The Quickstart gets you a Watcher Key, the desktop agent (or SDK), and your first experiment in the app.
3

Pick your path

No code → Ingest data with the Folder Watcher. Already have analysis scripts → Log directly with the Python SDK.
4

Process automatically

Attach a pipeline script so every new experiment gets metrics and plots without manual work.
5

Compare results

Use Analysis to overlay series across experiments, then turn the arrangement into a Report.
An experiment with no pipeline is still useful — it’s a plain data drop you can browse and download. Attaching a pipeline is what turns it into metrics and plots automatically.

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The app