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· Public charity

Cure International Inc

Cure's children's hospital network of eight hospitals provide life-changing and life-saving surgical care for children living with disabilities in a compassionate christian environment.

$102k
Granted FY2025still arriving
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Grants FY2025still arriving
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States reached
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Largest
01What it funds
01FY2025

Where the money goes

Grants by size, and the largest recipients.

$0
Median grant
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States reached
$96M
Total assets
02The need
02

Does the money reach high-need areas?

Each grant placed by the hardship in its grantee’s ZIP, against the area’s typical level.

Grants abroad, by region: $102k on the FY2025 return

Schedule F, as filed: 1 region. The IRS asks for region and purpose, not the recipient, so no country or grantee can be named here.

Sub-Saharan Africa$102k · 100% · 3 grants

Stated purpose: MEDICAL EQUIPMENT

How this is measured
US grants placed by each grantee’s ZIP, which can differ from where services are delivered. Need from public data (U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA), shown as context about the area, never attributed to the funder’s giving. Grants abroad on Schedule F are filed by region, purpose and amount with no recipient name, so they are shown by region and cannot be placed on the country map or matched to a grantee.
03Its field

Co-funders

Grantmakers whose grantees overlap with this funder’s far more than size alone predicts. Closer means stronger alignment; arcs show where they also fund each other. Here they form a tightly interlocked group: most of these funders back each other's grantees too.

International Aid IncMI15.7× affinity5 shared granteesties to 2 of 2Hover any node to trace its alignments.Compare side by side →

Open a dossier: International Aid Inc · Natl Christian Charitable Fdn Inc · Fidelity Investments Charitable Gift Fund

How this is measured
Affinity is a Gamma-Poisson posterior co-funding rate, re-centered on the typical rate, so thin evidence shrinks toward no signal. Overlap is association, not proof of shared intent.

On method. Every financial figure here is read from IRS e-file XML, the funder’s own 990/990-PF, each linked to its source. Grantee outcomes are each organization’s own program-service reporting (Form 990, Part III), read as association with funding, never as caused by it. Low-confidence name matches are suppressed rather than guessed. How we build these →

How this is measured
Each figure carries one of six labels. Filed is what the funder reported on its return. Official is another government record about an organization, such as a federal award or a charity register, joined by name where no shared identifier exists. Resolved is an identity we worked out where the filing named a recipient without an EIN, kept only above a measured confidence threshold. Computed is arithmetic over those, like themes, portfolio clusters and co-funder strength. Context is a statistic about a place rather than about an organization, which is what the need overlay is: it describes the area a grantee’s address sits in, not where its work lands. Inferred is drawn by a model from text, like the partnerships read out of public news and organization websites. Each is labeled where it appears.

Generated from the IRS Form 990 e-file return for fiscal year 2025, released 2025. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

Source object · view filing

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