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· Public charity

Discovery Triangle Development Corporation

Our goal is to work with community members to create an equitable food system that provides all communities access to healthy, affordable food to help everyone reach their highest potential.

$115k
Granted FY2019
5
Grants FY2019
1
States reached
$30k
Largest
01What it funds
01100% classified

What it funded, over time

Every grant placed by its stated purpose and the recipient’s mission, by year, FY2017 to 2019.

Science & Tech$178kHealth$150k
02FY2019 · 5 grants

Where the money goes

Grants by size, and the largest recipients.

$20,936
Median grant
1
States reached
$270k
Total assets
Largest grants
RecipientAmount
AVERY THERAPEUTICS$30,000
VAPOMETRY$30,000
TOUCHPOINT$20,936
THERASPECS$18,788
GT MEDICAL TECHNOLOGIES$15,000
02The need
03

Does the money reach high-need areas?

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

show:

Dollar for dollar, its grants (FY17–19) land where the poverty rate runs at 11%, against an area that typically sits at 9%. 100% of its dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 9%THERASPECS: $19k → 11%AVERY THERAPEUTICS: $30k → 15%THERASPECS: $11k → 11%SMART BRAIN AGING INC: $30k → 11%GT MEDICAL TECHNOLOGIES: $15k → 11%GT MEDICAL TECHNOLOGIES: $15k → 11%IRON HORSE DIAGNOSTICS INC: $25k → 11%IRON HORSE DIAGNOSTICS INC: $5k → 11%BIOSENSING INSTRUMENT INC: $22k → 11%BMSEED LLC: $22k → 11%BMSEED LLC: $8k → 11%BIOSENSING INSTRUMENT INC: $8k → 11%GEMEO BIOSCIENCE INC: $30k → 11%VAPOMETRY: $30k → 11%PHOENIX INTERFACE TECHNOLOGIES LLC: $28k → 11%TOUCHPOINT: $21k → 11%TOUCHPOINT: $9k → 11%0%20%40%50%more need →
grant to an above-average-need area below average· circle size = grant amount
How this is measured
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty line in the grantee’s ZIP, averaged from the tracts in that ZIP.
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.
03Its grantees
repeat funding

Who it funds again

Organizations funded in more than one year, against those funded once.

55%of every dollar goes to organizations it has funded before.
$180k · 6 repeat orgs$148k to everyone else

6 repeat relationships: 3 still active in FY2019, 3 since wound down; 2 grantees were first funded in FY2019 (too recent to call).

How the two cohorts compare

Re-uppedFunded once

Organizations

6
3

Total granted

$180k
$88k

Still filing today

0%
0%

New vs renewed · share of each year

In FY2019, 48% of grant dollars renewed an existing relationship; $60k went to new ones.

50%100%’17’18’19
RenewedFirst-time
How this is measured
First-time means a grantee’s first year in the filing window; renewed means funded in an earlier year too. The renewed share climbs naturally as a portfolio matures, so the signal is a year that bucks it (a wave of new grantees). 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

  • IH
    IRON HORSE DIAGNOSTICS AZ
    2× · 2017–2018 · $30k
  • T
    TOUCHPOINT
    2× · 2018–2019 · $30k
  • T
    THERASPECS
    2× · 2018–2019 · $30k

Funded once

  • GB
    GEMEO BIOSCIENCE INC
    one grant, 2018 · $30k
  • SB
    SMART BRAIN AGING INC
    one grant, 2017 · $30k
  • PI
    PHOENIX INTERFACE TECHNOLOGIES LLC
    one grant, 2017 · $28k
How this is measured

Repeat means funded in two or more distinct years. Growth and survival are read from each grantee’s own subsequent IRS filings.

04Its field
04the grantee network

1 grantees tracked through their own filings, 2017–2019.

Each grant beside the grantee’s revenue from every source, year by year.

How this is measured

Counted here: distinct organizations funded across 2017 to 2019, not grant rows in a single year, so this will not match the grant count on the cover. 1 of the 11 grantees resolved in that span have returns of their own we could reconcile.

Each grantee is resolved to its own IRS returns. Association, dated; never a causal claim.

0
Load-bearing (≥25% of a budget)
1
Early backer (in before they grew)
1/1
Grantees still filing
1/1
Grew since first funded

Where the money sits, by cause and then by grantee

IRON HORSE DIAGNOSTICS AZ: $30,000 · OtherIRON HORSE DIAGNOSTICS AZTOUCHPOINT: $30,000 · OtherTOUCHPOINTGEMEO BIOSCIENCE INC: $30,000 · OtherGEMEO BIOSCIENCE INCVAPOMETRY: $30,000 · OtherVAPOMETRYTHERASPECS: $30,000 · OtherTHERASPECSGT MEDICAL TECHNOLOGIES: $30,000 · OtherGT MEDICAL TECHNOLOGIESAVERY THERAPEUTICS: $30,000 · OtherAVERY THERAPEUTICSBMSEED LLC: $30,000 · OtherBMSEED LLCSMART BRAIN AGING INC: $30,000 · OtherSMART BRAIN AGING INCBIOSENSING INSTRUMENT INC: $30,000 · OtherBIOSENSING INSTRUMENT INCPHOENIX INTERFACE TECHNOLOGIES LLC: $28,295 · OtherPHOENIX INTERFACE TECHNOLOGIES LLC
Other$328,295

Each grantee by its size and the funder’s share of it; top left is load-bearing

25%50%75%100%grantee revenue →↑ funder's share of their budget
Grantee by grantee: a decade per organization, before and after funding

A decade per grantee: revenue shaded, grants as bars, all rows on one timeline.

On method. Every financial figure here is read from IRS e-file XML, the funder’s own 990/990-PF, and from the multi-year returns of the 11 grantees we resolved, 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 2019, released 2019. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

Possibly out of date. A more recent filing (FY2025) is on record and reports no grant expense, so the figures above are from FY2019, the most recent year this funder made grants.

Source object · view filing

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