Inside Grantx.
A look inside the intelligence engine that powers every recommendation.
The Problem with Traditional Search.
The grants landscape has a structural problem: the best-fit funder for your organization probably doesn't use the same words you do. A foundation supporting "mental health in adolescents" and "arts education" is a high-probability match for your music therapy program — but no keyword search will ever surface that connection.
The traditional approach — whether it's a database, a Google search, or a consultant's Rolodex — relies on exact terminology matching. It works when you already know who to look for. It fails when the best opportunities are hidden in the gaps between categories.
Grantx was built to close those gaps.
The Architecture.
Three layers. One engine.
The Leap.
From query words to eligibility signals.
The Proof.
The numbers behind the engine.
M+
Data points indexed from IRS 990s and federal sources.
<
min
Time from onboarding to a complete funding strategy.
K+
Active funders mapped in the internal knowledge graph.
%
Match accuracy measured against actual funding outcomes.
x
Better performance than standard search approaches.
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Organizations actively building strategies with Grantx.
The Comparison.
Three approaches. Different results.
Method
Keyword Tools
Standard AI
Grantx GRASP
Method
What it does
Accuracy
Time
Result