Grant decisions, on the record.
The grant-cycle problem
A grant cycle goes like this: open the call, get more proposals than expected, scramble together a review panel, run them through a spreadsheet, hold a long meeting, publish the winners, and brace for the follow-up questions.
The questions always come. Why did Project A get funded and Project B didn't, when both scored a 7 in the meeting notes? Why did the same panel give Project C a lower score the second time it was reviewed? Who decided the cap was £50K rather than £75K, and was that consistent across the cohort?
Most grantmakers can't answer these cleanly because the decisions live in three places: the spreadsheet, the meeting minutes, and Sue's memory.
What changes
Anonymised review by default
The reviewer sees the proposal, not the proposer. Institution names, applicant names, and country-of-origin metadata are masked during the scoring round. Identity is revealed only after the score is locked.
Proposal scoring with citations
Every criterion-level score points at the section, page, or budget line in the proposal that justified it. A reviewer (or a year-later auditor) can re-trace the reasoning without re-reading the whole proposal.
Conflicts-of-interest, declared and enforced
Reviewers declare conflicts before they see the proposal list. The platform routes conflicted proposals away automatically and logs the routing decision, so the audit trail shows not just who reviewed what but who was kept away from what.
For the panel vs. for the funder
What the panel sees
A structured view of each proposal: executive summary, criterion scores with evidence citations, budget cross-check, and the AI's flagged risks (over-scoped milestones, missing co-investigator CVs, mismatched budget categories).
Panel meetings shift from “here's what I remember about this proposal” to “here are the three places I disagreed with the AI.”
What the funder gets at the end
A full cohort report: every funded proposal, every rejected proposal, the score distribution, the reviewer-disagreement map, the conflict-of-interest log, and a fairness analysis comparing outcomes across institution type, country, and applicant seniority.
The report writes itself from the audit trail. Board packs stop being a week of consultant work and become a download.
Post-award is part of the platform
When a grant is awarded, the grantee gets a magic-link portal. Quarterly milestones, expenditure updates, and outcome publications all flow back into the same record the panel reviewed.
Two cycles in, you have something most grantmakers don't: a longitudinal view of which scoring patterns correlate with which outcomes. The next cycle's rubric writes itself from the last cycle's data.
What FairLens isn't
FairLens isn't a grants-management system. It doesn't handle disbursement, contracting, or statutory tax reporting. Those live in your finance stack, and FairLens hands the finalised decision record to them via the API or CSV export.
It also isn't a substitute for the panel. The AI suggests; the panel decides. Every override is logged with a reason. If the panel wants to fund the proposal the AI ranked 47th, they can. They just have to write down why.
Run your next call for proposals on FairLens.