Workspace separation
Each client workspace is organized around its own organization, users, units, module access, and active fund dataset. Admins decide which people can see which parts of the fund universe.
Data privacy and security
Built for sensitive fund work without unnecessary data sprawl.
FundNav is designed around a simple principle: institutions should be able to use powerful fund decision tools without handing over more information than the work requires.
How FundNav handles data
A current workspace, not a permanent data warehouse.
FundNav keeps what the workspace needs to function and avoids preserving generated work unless a user intentionally saves it.
Current-state data model
Each university is connected to one primary uploaded file controlled by its university administrators. FundNav does not retain this file, and it can be modified exclusively by administrators. This helps prevent outdated information from being used or sensitive information from being made available to unapproved parties.
Limited user retention
Most tool outputs are intentionally not preserved after refresh unless a user chooses to save, export, or copy them. Saved queries, saved exclusions, user access, and account settings persist because users need them to work.
Role and unit controls
Admins can update user access by unit and by module. End users only see the funds, balances, and tools made available to them.
No resale or secondary use
FundNav does not sell institutional data, use it for advertising, build external datasets from it, or repurpose it outside the workspace tools clients choose to use.
Minimum necessary data
Core fund intelligence does not require donor identities or student records. When a client uses scholarship matching, they control which student attributes are uploaded and should use the minimum detail needed for the review.
AI-enabled workflows
Secure API use, reviewed outputs.
FundNav uses AI where interpretation, comparison, summarization, or drafting can remove friction. The product still expects human review, especially for awards, fund use decisions, and agreement language.
AI-enabled requests are sent through our AI model’s API so FundNav can interpret fund language, compare criteria, draft, and summarize.
Data sent through our AI model’s API is not used to train the AI model or related products.
FundNav sends the information needed for the requested workflow, such as selected fund purpose language, balances, student attributes supplied by the client, or agreement text.
Generated outputs are decision-support materials. Users should always review results before acting, exporting, sharing, awarding, signing, or presenting anything externally.
Questions welcome