Getting Started

1. Create a Project

1. From the projects screen, select New Project.
2. Give the project a clear study, client, or research-question name.
3. Add a description, labels, and the citation style you expect to use.
4. Open the project. The guided tour can introduce the current interface and can be replayed from Help.

Keep unrelated studies in separate projects. Project-scoped memory, literature context, and artifacts are designed to remain inside that research boundary.

2. Add Research Data

Open Files and select Upload (a file or a whole folder), or pressCtrl/Cmd+U.

There is no per-file upload size limit on any plan; files above 64 MB upload directly to storage in parts. Compressed archives are additionally protected by archive and decompressed-size safety limits. See Data Management for the full guide.

3. Learn the Project Workspace

Use Ctrl/Cmd+Kfor the command palette, Ctrl/Cmd+1for Files, and Ctrl/Cmd+2for Chat.

4. Choose an Analysis Mode

Use the model control in the composer; /standard switches back to Standard. Mode names describe CATO behavior; underlying providers may change without altering your workflow.

5. Ask a Grounded Question

Attach or select the exact evidence CATO should use. Type @ to mention a dataset and / to browse available commands. Ask for a plan first when you want a reviewable approach before execution.

A strong prompt states the question, relevant variables, population or subset, desired method, required checks, and output format. If a definition is ambiguous, ask CATO to confirm it before running code.

6. Follow Long-Running Work

CATO persists active response streams and background sandbox jobs. You can move to another conversation or reload the page and reconnect to the same run. Background job cards show progress, completion, artifacts, failures, and cancellation controls.

• Use Cancel when the question or data selection is wrong.
• Do not submit the same request repeatedly while a run is reconnecting.
• If generation stops, reopen the conversation first; durable output may already be recoverable.
• Billing and usage limits can interrupt work mid-run; the interface preserves the useful partial state when possible.

7. Inspect and Refine Artifacts

Open generated files and figures in the Workspace instead of treating the chat message as the final record. CATO stores artifact provenance, versions, execution context, and the conversation that produced the output.

If an editor reports unsaved changes, save or discard them before switching versions or closing the artifact. Reviewer findings and annotations are guidance, not a replacement for validating data, code, statistics, and citations.

8. Search and Curate Literature

Use Literature → Deep Search to ask one ranked question of the scholarly literature, then save relevant works to the Library. CATO returns up to 100 results in relevance order, collapses a preprint and its journal version into one record, can retrieve available full text, and supports evidence extraction, networks, watches, and document generation.

Fetched papers can open in the Workspace and selected literature can be sent to Chat as a bounded context packet. Always verify bibliographic details and source-grounded claims before publication. See the Literature Intelligence guide.

9. Control Memory

Memory can retain stable preferences and facts grounded in your messages. Project memory stays with one project; global memory can apply across projects. Review memory settings to enable or disable recall, automatic learning, and cross-project use, and edit, pin, or delete individual entries.

Plans, Uploads, and AI Usage

Billing in Settings is the source of truth for your account, taxes, current prices, usage, renewal date, and any institutional or negotiated terms. Included AI usage is a rolling allowance measured over 5-hour and 7-day windows, not a fixed message count; usage frees up as earlier activity ages out of the window. Enterprise plans are arranged by agreement.

Next Steps