CollabHub
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Getting started

From a blank browser tab to your first timestamped attribution in about five minutes. The app walks you through most of this the first time you sign in — this page is the map of the same journey.

1Create your account

Sign up with your email and a password — or use one of the single sign-in buttons shown on the form (Google, GitHub, or Apple, depending on what your CollabHub has enabled). Email sign-ups get a verification link — click it and sign in.

2Set up your workspace

On first sign-in, a short setup wizard takes over: confirm where your data should live (data residency — part of CollabHub’s GDPR-ready data management), fill in your research profile, and create your first workspace. A workspace is your lab’s home — notebooks, datasets, protocols, and experiments all live inside one, and you can invite collaborators to it whenever you’re ready.

The wizard then offers a starter kit: pick your discipline and it seeds one protocol, one notebook entry, and one sample dataset into your new workspace, so you land on real content instead of an empty shell. Skip it any time.

3Write your first notebook entry

Open Notebook in the sidebar and create a new entry. The editor handles rich text, tables, code, LaTeX equations, and inline embeds of your datasets, protocols, and files — so an entry can be a full experimental record, not just notes.

4Add a dataset

The wizard’s upload step (and later, Datasets → Upload dataset in the sidebar) takes a delimited-text file — .csv, .tsv, .tab or .txt — and turns it into a versioned dataset. (Excel workbooks: save as CSV first.) Coming from another tool? The importer brings in a CSV/TSV export or your whole Benchling tenant, with a dry-run preview first — see Import your data.

5Run an agent

Open Agents and pick one — the Data Assistant is a good first run. Point it at the dataset you just added and ask a question; the run and its output are saved to your run history, and agent answers can be embedded straight into notebook entries.

6Your first timestamped attribution

You already have it. Every notebook entry, dataset, protocol, experiment, observation, and file you create is automatically sealed with a timestamped, SHA-256 cryptographic proof of what existed and when — no extra step. Open Priority in the sidebar to see your proof timeline, and download a certificate for any record. When your work is shared and reused, attribution stays attached — free sharing with attribution is built into the platform.

Where next?