· Private foundation
Infosys Foundation USA
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 $10k15 grants · $51k
- $10k–50k37 grants · $671k
- $50k–250k23 grants · $2.2M
- $250k+2 grants · $606k
| Recipient | Amount |
|---|---|
| CodeJoy LLC | $355,900 |
| Code Org | $250,000 |
| Computer Science Teachers Association | $155,000 |
| One10 LLC | $150,500 |
| Kode with Klossy | $150,000 |
| Raspberry Pi Foundation North America | $150,000 |
| One10 LLC | $150,000 |
| One10 LLC | $125,500 |
| Individual grant recipient | $119,250 |
| Codejoy LLC | $101,600 |
| Trustees of Indiana University | $100,000 |
| Boys & Girls Club of Hartford Inc | $93,000 |
| Opera on Tap | $90,000 |
| Miami EdTech Inc | $84,362 |
| Pencil Inc | $80,000 |
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 human-services grants (FY17–25, $136k) land where the poverty rate runs at 12%, against an area that typically sits at 10%. 93% of those dollars go to grantees based in above-average-need neighborhoods. Most of your grants land in higher-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.
Which US states your grants reach
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.
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.
49 repeat relationships — 28 still active in FY2025, 21 since wound down; 37 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, 69% of grant dollars renewed an existing relationship; $1.1M 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
- DDONORSCHOOSEORG7× · 2017–2024 · $2.7M · revenue +24%
- CSCOMPUTER SCIENCE TEACHERS ASSOCIATION LLC8× · 2017–2025 · $2.0M · revenue +487%
- RIREADYCT INC5× · 2021–2025 · $291k · revenue +343%
Funded once
- KWKode with Klossyone grant, 2023 · $259k
- GSGIRL SCOUTS OF THE UNITED STATES OF AMERICAone grant, 2019 · $250k · revenue +22%
- NYNEW YORK ACADEMY OF SCIENCESone grant, 2017 · $244k · revenue -13%
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.
Ai4all's mission is to ensure that the next generation of ai leaders reflects humanity. ai4all is transforming the pipeline of ai practitioners who will shape ai for the benefit of humanity.
Techcongress gives talented technologists the opportunity to gain first-hand experience in federal policymaking and shape the future of tech policy through fellowships with members of congress and congressional committees.
The concord consortium innovates and inspires equitable, large-scale improvements in stem teaching and learning through technology...(continued on schedule o)
To provide leadership and support for the national effort to increase the representation of successful african american, native american and latinx women and men in engineering and technology, math, and science-based careers.
Dfsme's mission is to strengthen science, technology, engineering, and mathematics education to prepare all delaware students to be informed citizens and competitive in the global workforce.
Achieving international impact through world-class research and education in fundamental computer science and information technology.
To create and inspire better ways to give every student an educational foundation for lifelong success. we imagine a world where every student attends a school that meets them where they are, adapts to the unique ways they learn, and…
The common application is a not-for-profit membership organization of over 1,100 colleges and universities across the globe committed to access, equity, and integrity in the college admission process. every year, over 1.5 million students…
The organization's mission is to prepare students for opportunities available at the intersection of technology and sports.
The mission of the silicon schools fund is to improve education through supporting the launch of excellent new schools, improving academic instruction in existing schools, and by funding some of the boldest innovations in education…
To propel youth to thrive in a technology driven world.
For reference, the grantee most central to the portfolio’s shape is Education Training and Research Associates and the most unlike its peers is Quorum Outreach and Research Foundation. Resemblance is measured on each organization’s own IRS 990 mission text; it reflects how work is described, not its quality or impact.
For each theme you fund, this compares how the sector’s money is shifting with how your own giving is shifting.
Sector change and giving change are each shown relative to their own range, growing (right) or shrinking (left); both normalized, so inflation isn’t mistaken for growth.
Your grantees are a median of 22 years old; the field is 16. You back the established end — and your money leans older still.
The field is 22% startups (under 5 years old) — 0% of your grantees by number, and just 0% of your money.
The orgs you fund almost never close — 0.7% lost their exemption, against 13% of the field you don’t fund.
Age = years since IRS exemption (a founding proxy). “Closed” = auto-revocation for 3 years of non-filing — a floor on closure, not proof, and bigger established orgs lapse least. Association, not causation.
119 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. 119 of the 268 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
Showing your 200 largest grantees by grant value.
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 CODEORG ↗
- Who funds DONORSCHOOSEORG ↗
- Who funds COMPUTER SCIENCE TEACHERS ASSOCIATION LLC ↗
- Who funds MV GATE INC ↗
- Who funds Teach for America Inc ↗
- Who funds THE BOYS AND GIRLS CLUBS OF HARTFORD ↗
- Who funds OPERA ON TAP ↗
- Who funds PENCIL INC ↗
- Who funds BLACK GIRLS CODE INC ↗
- Who funds KODE WITH KLOSSY INC ↗
- Who funds READYCT INC ↗
- Who funds Hispanic Heritage Foundation ↗
- Who funds DIGITAL PROMISE GLOBAL ↗
- Who funds NEW YORK CITY FOUNDATION FOR COMPUTER SCIENCE EDUCATION INC D/B/A CSFORALL ↗
- Who funds ASSOCIATION FOR COMPUTING MACHINERY INC ↗
- Who funds GIRL SCOUTS OF THE UNITED STATES OF AMERICA ↗
- Who funds NEW YORK ACADEMY OF SCIENCES ↗
- Who funds Thurgood Marshall College Fund ↗
- Who funds TELEVISA FOUNDATION INC ↗
- Who funds CICP FOUNDATION INC ↗
- Who funds FRIENDS OF THE BRITISH COUNCIL USA ↗
- Who funds THE UNIVERSITY OF TEXAS FOUNDATION INC ↗
- Who funds TECH KIDS UNLIMITED INC ↗
- Who funds THE AMERICAN INDIA FOUNDATION ↗
- Who funds Carnegie Mellon University ↗
- Who funds RASPBERRY PI FOUNDATION NORTH AMERICA INC ↗
- Who funds THE UNIVERSITY OF FLORIDA FOUNDATION INC ↗
- Who funds Project Invent ↗
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 tightly interlocked camp — most of these funders back each other's grantees too.
Open a dossier: Silicon Valley Community Foundation · Tides Foundation · Pwc Foundation Inc · Akamai Foundation Inc · Intel Foundation · Motorola Solutions Foundation · Broadcom Foundation · Glenn W Bailey Charitable Trust · Pinkerton Foundation · Hispanic Federation Inc · Hartford Foundation for Public Giving · Scratch 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 Infosys Foundation USA 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, a single department, or state — and drag the year to watch it move.
- Girls for Technology Inc — 80% of income from government
- Readyct Inc — 61% of income from government
- Massachusetts Institute of Technology — 35% of income from government
- Kiss Institute for Practical Robotics — 30% of income from government
- The Boys and Girls Clubs of Hartford — 20% of income from government
- Televisa Foundation Inc — 18% of income from government
- Moco Kidsco Inc — 15% of income from government
- Citizen Schools Inc — 8% of income from government
- Girl Develop It — 7% of income from government
- Digital Harbor Foundation — 2% of income from government
- Girl Scouts of Connecticut Inc — 2% of income from government
- Sacred Heart University Incorporated — 1% of income from government
- Collegiate Pathways Inc — 1% of income from government
- The Possible Project Inc — 0% of income from government
- Eli Whitney Museum Inc — 0% of income from government
- South Tech Charter Academy Inc — 0% of income from government
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.
Warm introductions · Powered by PlinthPlus
How do I get to Infosys Foundation USA?
Find your warmest path to Infosys Foundation USA through trustees and officers whose names appear on both boards. Search for your organization and Plinth traces the shortest route it can evidence.
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.