· Private foundation
Kamlaben & Raojibhai Patel Family Foundation Inc
Its FY2025 filing reports that it funds preselected organizations and did not take unsolicited requests; check the foundation's own site before ruling it out.
What you funded, over time
Every grant placed by its stated purpose and the recipient’s mission, by year — across FY2017–2025.
Where the money goes
Your grants by size, and where they go.
By grant size · FY2025
- Under $10k16 grants · $50k
- $10k–50k2 grants · $40k
- $50k–250k1 grant · $199k
| Recipient | Amount |
|---|---|
| BAPS | $199,306 |
| Individual grant recipient | $30,000 |
| ECO FOUNDATION HORIZON SCHOOL | $10,000 |
| HOFSTRA UNIVERSITY | $5,988 |
| KENT SCHOOL ANNUAL FUND | $5,000 |
| SHREE VALLABH GAUSHALA TRUST | $5,000 |
| BAPS | $4,304 |
| SANKRA EYE FOUNDATION | $3,000 |
| INDIA CULTURAL SOCIETY | $3,000 |
| HINDU ANATH ASHRAM NADIAD | $3,000 |
| INDORE SOCEITY OF MENTALLY CHALLENGED | $3,000 |
| BERGEN COMMUNITY COLLEGE FOUNDATION | $3,000 |
| Individual grant recipient | $3,000 |
| SHARE AND CARE FOUNDATION | $3,000 |
| Individual grant recipient | $3,000 |
Do your dollars go where the need is?
Each grant placed by the hardship in its grantee’s ZIP, then read against the area’s typical level.
Your US giving — 89% of grant dollars ($1.6M). The need read here covers only this US portion; the 11% that went abroad ($193k) is mapped below.
Dollar for dollar, your grants (FY17–25) land where the poverty rate runs at 8%, against an area that typically sits at 11%. 5% of your dollars go to grantees based in above-average-need neighborhoods. Your grants skew toward lower-need ZIPs.
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty linein the grantee’s ZIP, averaged from the tracts in that ZIP; grantee ZIP can differ from where services are delivered.
Beyond the US — 11% of all-years giving ($193k)
1 country, by the recipient’s country on the filing.
US grants placed by each grantee’s ZIP, which can differ from where services are actually delivered. Need from public data — U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA — shown as context about the area, never attributed to your giving. International giving is mapped by the recipient’s country from the same 990 filings; comparable need data isn’t available at that grain.
Who you back again
Which organizations you funded more than once, and which you funded a single time. Each grantee is matched to its own filings.
24 repeat relationships — 16 still active in FY2025, 8 since wound down; 2 grantees were first funded in FY2025 (too recent to call).
How the two cohorts compare
Organizations
Total granted
Median revenue growth · since first grant
Still filing today
New vs renewed · share of each year
In FY2025, 88% of grant dollars renewed an existing relationship; $36k went to new ones.
Where new relationships form · theme of each grantee’s first grant
First-time = a grantee’s first year in your filing window; renewed = funded in an earlier year too. As a portfolio matures the renewed share naturally climbs — once funded, an org stays “renewable” — so the signal is the years that buck it (a new-grantee intake wave). The earliest year is left-censored: relationships that predate the data read as “new.” Theme is the grantee’s IRS cause.
Backed again, and grew
- BCBERGEN COMMUNITY COLLEGE FOUNDATION4× · 2018–2025 · $15k · revenue +6%
- EVEKAL VIDYALAYA FOUNDATION OF USA2× · 2018–2019 · $11k · revenue +22%
- MSMUNI SEVA CHARITABLE FOUNDATION USA INC3× · 2023–2025 · $7k · revenue +15%
Funded once
- IGIndividual grant recipientone grant, 2018 · $8k
- GBGITA BHAWAN TRUSTone grant, 2017 · $7k
- NDNARGIS DUTT MEMORIAL FOUNDATIONgraduatedone grant, 2018 · $5k · revenue +42%
Repeat = funded in two or more distinct years; growth and survival are read from each grantee’s own subsequent IRS filings.
The map has a center of gravity: the average direction from the rest of the sector toward the organizations the foundation funds — the shape of its giving. Scoring every nonprofit along that direction surfaces the ones that look most like the portfolio. These are the closest matchesthat aren’t grantees — a resemblance in what they say they do, not a recommendation.
Public education
Educate children in need
The organization funds a scholarship fund for disbursement to qualified students to pay for educations costs at educational campus changa
Empower education to less fortunate and provide various support fromm food and various other support in rural india
Helping deserving students by giving the scholarships.
The manav seva mandir is a hindu religious institution in the greater chicagoland area. not only is it an excellent place of worship, but it also renders a social atmosphere and a cultural center that preserves and promotes our hindu…
For reference, the grantee most central to the portfolio’s shape is Share and Care Foundation for India and the most unlike its peers is Pradeep & Usha Tandon Family Foundation Inc. Resemblance is measured on each organization’s own IRS 990 mission text; it reflects how work is described, not its quality or impact.
11 grantees tracked through their own filings, 2017–2025.
Each one resolved to its own IRS returns and tracked year by year — your grant beside their revenue from every source. Association, dated; never a causal claim.
Counted here: distinct organizations you funded across 2017–2025, not grant rows in a single year — so this will not match the grant count on the cover. 11 of the 36 grantees resolved in that span have returns of their own we could reconcile; the rest are funded organizations whose filings we could not track year by year.
Where your money sits — by cause, then by grantee
Each org by its size and your share of it — top-left is where you’re load-bearing
Go grantee by grantee — a decade per org, and how each moved after you funded them
A decade per grantee — revenue shaded, your grants as bars, all rows on one timeline.
- Who funds THE ROTARY CLUB OF RIDGEWOOD AM ↗
- Who funds SHARE AND CARE FOUNDATION FOR INDIA ↗
- Who funds INDIA CULTURAL SOCIETY ↗
- Who funds BERGEN COMMUNITY COLLEGE FOUNDATION ↗
- Who funds EKAL VIDYALAYA FOUNDATION OF USA ↗
- Who funds MUNI SEVA CHARITABLE FOUNDATION USA INC ↗
- Who funds HOFSTRA UNIVERSITY ↗
- Who funds NARGIS DUTT MEMORIAL FOUNDATION ↗
- Who funds PRADEEP & USHA TANDON FAMILY FOUNDATION INC ↗
- Who funds MERCY FOR ANIMALS INC ↗
- Who funds INDIAN CAUCUS OF SECAUCUS ↗
The grantmakers whose grantees overlap with yours far more than size alone predicts. Each orbits closer the stronger the alignment; the arcs between them show where they also fund each other. Here it reads as a set of overlaps that mostly run through you, not between each other.
Open a dossier: Verizon Foundation
Affinity is a Gamma-Poisson posterior co-funding rate, re-centered on the typical rate, so thin evidence shrinks toward no signal. A research starting point: overlap is association, not proof of shared intent.
Government reliance of your grantees
Every dot is one organization Kamlaben & Raojibhai Patel Family Foundation Inc funds. Left–right is the share of its income from government; up–down is the share from you. Bigger dots raise more. Filter to federal or a single department — and drag the year to watch it move.
Government income is each org’s traced federal awards (USASpending — grants and contracts) plus state payments (open checkbooks) as a share of its total revenue (IRS Form 990); the self-reported government-grant line (990 line 1e) is carried for cross-check: a grantee that reports government grants we could not trace to a source is left off the chart rather than shown as receiving none. An association, not a claim that your grant caused the public funding. Coverage is precision-first — a floor, not a census; state records exist for 9 states, so a grantee outside them shows no state figure (dimmed) rather than a false zero. Federal award amounts are obligations, which can span years, so a single-year share is indicative. 990 filings lag 12–24 months.
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Each link is a name appearing on two organizations’ public IRS 990 filings, matched on that name and, where the filings support it, on location. A same-state match has geographic support, which is a second matching feature rather than confirmation that the two are one person; a cross-state one is the likeliest to be two people who share a name. Every hop shows its tier, low-confidence and distant paths are held back rather than guessed, and it is worth confirming the person before you use the introduction.