Grant guide

Match score: a triage signal, not a funding prediction

A match score helps prioritise opportunities. It should explain why a grant may fit an organisation, not pretend to predict a funder's final decision.

Best for

Teams deciding where to spend application time

Teams using AI-assisted funding matching and deciding which opportunities deserve review time.

Use this page to

Make the first review more concrete

Understand what a grant match score means and how to use it.

Review workflow

What FundingLens helps you do

Keep source facts, caveats and next actions together so your team can decide what deserves attention before application work starts.

01

Score hard blockers first: applicant type, geography, project scope, eligible costs, deadline and minimum evidence.

02

Then review softer fit signals such as strategic alignment, beneficiaries, delivery capacity, budget realism and evidence strength.

03

Keep match score, confidence score and human review status separate so teams can see both fit and uncertainty.

Readiness checks

  • Eligibility blockers checked before fit scoring.
  • Source criteria cited beside the score.
  • Budget, deadline and readiness risks included.
  • Confidence and caveats shown separately.
  • Human review required before application decisions.

Eligibility caveats

  • A match score is not an award prediction.
  • Funders may reject eligible, high-quality applications because demand exceeds budget.
  • Scores should change when source facts, deadlines or organisation profiles change.

Source references

Related FundingLens pages