Turn protocols into structured, runnable workflows.

Upload raw protocol files, start from a standard library, and keep every change versioned so the exact method behind each experiment stays clear.

Collect FAIR data without hassle. Leverage your experimental history to design better experiments and interpret results.
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Upload raw protocol files, start from a standard library, and keep every change versioned so the exact method behind each experiment stays clear.


Keep the hypothesis, plan, run context, result files and conclusion together. Handwritten notes become structured records without slowing down work at the bench.


Link related experiments so the pilot result leads directly to validation and the next study. Your full research history stays understandable in one view.

Everything stays connected
Import and organise reusable methods as clear, runnable protocols.
Know the exact protocol version behind every experimental run.
Express steps, decisions and repeats as a workflow the whole lab can follow.
Set run parameters and move through the protocol one action at a time.
Keep notes, deviations and result files beside the step that produced them.
Bring hypotheses, plans, runs, results and conclusions into one record.
See how pilots, validations and follow-up experiments connect in one graph.
Trace created samples back to the protocol run that produced them.
Search samples across nested lab locations, including addressable plates.
Your sous chef at the bench
Bring protocols, experiment records and research context into one connected workflow.
Wet-lab teams that want an easy, consistent way to record their methods and results, and who want powerful, scientifically grounded AI to refine their experimental plans and conclusions.
Unlike a static document, Sous keeps every experiment linked to the exact protocol version used and records changes made at the bench.
Yes. Sous can parse handwritten notes and fold them into the experiment record automatically, so you are not forced to type everything in real time. Write how you write; the structure gets added for you.
Sure. AI features are only ever triggered if you call for them.
Yes. Sous will always have a free plan for academic labs. We may charge for optional bonus features in the future, but the core academic workflow will stay free.
Sous draws on two sources: published scientific literature and your own experimental history. When you are planning experiments or interpreting a result, Sous analyses both to provide suggestions in context.
Your data is not used to train models. Raw data and unpublished results stay private to your team until you choose otherwise. If you choose to use LLM-powered suggestions, then experimental plans and conclusions (but no raw data) may be shared with third-party LLM providers under terms that do not allow them to use that information.
Access is tied to authenticated accounts and organisation membership. Experiment records, protocols, runs, notes, and result files are stored behind row-level security policies, so users can only read or change data for organisations they belong to. Admin-only actions, such as deleting some shared records, are checked separately.
Each core record carries an organisation ID, and database policies check membership before returning or accepting changes. PowerSync uses the same organisation membership boundary when deciding what data to sync to a device, so a user only receives the local working set for teams they can access.