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- Track cost. Compute hours, compute cost, and storage cost for the project.
- Set and share out budgets. Give each member an allocationa spending limit. The platform blocks giving out more than the project holds. (The project's total is set by the platform team, after the funds reach the Science Cloud.)
- See platform usage. Who is using what, and how much.
- Manage members and roles. Add members, remove members, and promote a member to project admin.
- Turn on collaboration. The project-level switch described above.
- Cross-account AWS access. Register one of your own AWS roles, and the platform hands it to your notebooks at start-up. With it you can use any AWS service in your own account from the Research Platform — for example, start an HPC cluster there, or read a mission bucket. (HPC means high-performance computing: a large group of machines for heavy jobs.) No access keys are copied, and no secrets sit in a notebook.
- Audit trail. Every account, membership, and budget change, with who did it and what changed.
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- Scored AI tools. Every tool in the catalog scored for quality and safety, with history.
- Plain-language search. Find a model, agent, or tool by describing what you need.
- Budget stop at launch. Show a true remaining balance, and stop new workspaces when the project's money is used up, and let a project admin choose whether a member who passes their own limit is blocked or may keep spending from the project's pool.
- Storage cost per person. See what each member's object storage costs.
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