1. Find funding information
FundRobin revisits public funding sources and processes likely opportunities rather than relying on one static directory.
- Coverage varies by source and region.
- The original funder remains authoritative.
Funding intelligence, explained
How FundRobin Works
FundRobin connects discovery, verification, eligibility, matching, grounded research and proposal work. The important distinction is that AI does not replace the evidence or the decision: source material and organisation context shape the workflow, while people remain responsible for the final judgement.
2. Turn calls into structured intelligence
Opportunity pages and supporting material are converted into structured information such as funder, deadline, amount, geography and eligibility details.
- Completeness controls reduce weak inputs before matching.
- Extraction can still be incomplete when source material is unclear.
3. Screen eligibility before strategic fit
Hard eligibility conditions are considered before deeper AI fit analysis. That lets FundRobin prioritise opportunities worth investigating instead of presenting another undifferentiated keyword list.
4. Explain the recommendation
Matches can include plain-English reasoning using available organisation and opportunity context. A match is a prioritisation aid, not a guarantee of eligibility, funding or success.
5. Adapt to explicit feedback
When a user marks a recommendation as not relevant and explains why, actionable constraints can be carried into organisation matching preferences and influence future refreshes.
6. Ground research in real material
Robin can retrieve opportunity facts, organisation context, match context and relevant source-document passages before answering detailed questions, with source links where available.
7. Keep people in control of proposals
FundRobin can assess requirements, structure an outline and help draft sections. Team Notes, AI summaries and proposed edits remain reviewable; suggested changes are previewed before a user saves them.