Skip to content
CollabHub.ai
Sign inGet started

Getting started

From a blank browser tab to your first timestamped priority proof 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.

  1. Create 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.

  2. Set up your workspace

    On first sign-in, a short setup wizard takes over: confirm where your data is stored (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.

  3. Write 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.

  4. Add 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.

  5. Run an agent

    The setup ends with the Data Assistant working on the sample dataset. Later, open Agents, point it at your own dataset and ask a question. Every run and its answer are kept in your run history, and you can embed an answer straight into a notebook entry.

  6. Your first timestamped priority proof

    You already have it. Every notebook entry, dataset, protocol, experiment, observation and file you create is recorded with a timestamped SHA-256 priority proof of what existed and when, with no extra step. Open Priority proofs in the sidebar to see your timeline and download a certificate for any record. Anyone can check a certificate on its public verification page. When your work is shared and reused, the attribution stays attached.

Where next?