Trust centre

Security, Privacy and AI Data Use

FundRobin should earn trust through the controls it actually operates—not through absolute promises. This page explains the current public security and data-use model in customer language, including where important limitations still apply.

How FundRobin works →Privacy policy →Methodology & limitations →

The short version

Private product data is handled within organisation-scoped workflows. FundRobin uses managed infrastructure and encrypted transport. AI receives relevant context when a user asks for an AI-assisted function; customer content is not used to train FundRobin’s own commercial models. Provider-specific retention or training guarantees are only stated when verified for the active provider configuration.

Organisation-scoped access

Private customer workflows are designed around organisation context and access controls so users operate within the organisation they are authorised to use.

  • Organisation context is carried through private product workflows.
  • Database access controls are part of the application security model.
  • Access-control design reduces cross-organisation exposure risk; it is not a claim that software can never contain a defect.

Encryption and managed infrastructure

FundRobin uses managed cloud services and encrypted transport for customer-facing traffic. Sensitive operational credentials are kept out of public website content and should be managed through the relevant secret-management controls.

  • HTTPS protects data in transit between supported clients and services.
  • Managed infrastructure provides platform security controls and operational monitoring.
  • Security remains a shared operational responsibility, not a one-time certification claim.

What FundRobin stores

FundRobin stores the data needed to provide the service: organisation and user context, funding and matching records, proposal workflow data, collaboration records and operational metadata where those features are used.

  • Public funding-source data is distinct from private organisation/customer data.
  • Private opportunity and document workflows are scoped to the owning organisation.
  • Operational records can support traceability, but they should not be described as a complete immutable customer audit trail.

How AI uses customer context

When a user requests an AI-assisted function, FundRobin may send the relevant prompt and context needed to perform that function to configured AI providers. FundRobin does not use customer content to train or fine-tune its own commercial models.

  • Only the context required for the requested workflow should be assembled for the model call.
  • AI outputs can be wrong and remain subject to user review.
  • Provider-specific training, retention and residency statements are only made where the current provider configuration and contractual terms have been verified.

Human control in AI workflows

AI assistance is designed around reviewable actions rather than silent autonomous submission. Matching exposes rationale; proposal work is section-based; AI-proposed edits can be previewed before a user saves them.

  • A match score is a prioritisation signal, not an award or eligibility guarantee.
  • Grounding and source links reduce uncertainty but cannot eliminate model error.
  • Applicants remain responsible for final facts, claims, eligibility and submission requirements.

Retention, deletion and operational limits

Retention depends on the type of record and the service needed to provide the product. Deletion and retention commitments should be read together with the current Privacy Policy and applicable account terms rather than inferred from a blanket “nothing is stored” promise.

  • FundRobin avoids universal zero-retention claims that are not true across every workflow and provider.
  • Backups, logs and operational recovery mechanisms can have different lifecycles from primary application records.
  • Material provider or infrastructure changes should be reflected in this page when verified.

Security questions or responsible disclosure

If you have a security, privacy or data-use question that is not answered here, contact FundRobin rather than relying on an inferred technical promise. Responsible reports are reviewed against the current implementation and operating environment.

contact@fundrobin.com Contact FundRobin →