1. Our Mission
ThinkKits collapses the information gap between schools and the federal funding they deserve. All data we use is publicly available — we just do the work of finding it, connecting it, and surfacing it when it matters.
We serve two audiences with complete transparency:
- Schools: We are a funding discovery engine for you — we help you find money you're leaving on the table.
- Vendors: We help you find schools with active funding signals — this is built on public data, not secret intelligence.
This page proactively addresses the #1 trust barrier: "How do you know this about my school?" Every claim we make is traceable to a public source. Every signal we surface is an inference from verifiable data, not a secret database.
2. What We Know and How We Know It
Every data point in ThinkKits comes from verified, publicly available federal and state sources. Below is a complete catalog of what we use, what it tells us, how current it is, and our confidence level.
NCES Common Core of Data (CCD)
nces.ed.gov/ccd105K+ schools, enrollment, demographics, Title I status, grade span, locale type, charter/magnet status.
USAC Open Data (E-Rate)
opendata.usac.orgE-Rate commitment letters, Category 2 budgets, vendor history, discount rates, FRN status, disbursements.
USASpending.gov
usaspending.govFederal award data, grant history, unobligated balances, recipient details, CFDA program codes.
Census SAIPE
census.gov/programs-surveys/saipePoverty/income estimates for Title I allocation formulas. District-level poverty rates, estimated school-age children in poverty.
USDA Direct Certification
fns.usda.govMedicaid, SNAP, TANF matching rates by state. Aggregate eligibility rates from public USDA reports — we do NOT use individual student records.
FRAC CEP Database
frac.orgCommunity Eligibility Provision ISP (Identified Student Percentage) rates. Used to identify schools near the 40% CEP threshold.
State Board Minutes (via PACER)
Public recordsApproved purchases $12K+, budget discussions, curriculum adoptions, contract approvals from public LEA meeting records.
EDFacts
ed.gov/edfactsAcademic performance, proficiency rates, chronic absenteeism, graduation rates, school improvement status.
3. How We Build Funding Signals
Funding signals are INFERENCES from public data, not confirmed facts. Each signal has a confidence tier that tells you how certain we are. We never claim to know something we don't.
Understanding Confidence Tiers
Every signal is labeled with one of three confidence levels: VERIFIED (confirmed via direct source), ESTIMATED (calculated from public formula), or DIRECTIONAL (pattern match from demographic/historical data). See Section 8 for full definitions.
3.1 E-Rate Category 2 New Cycle
What We Identify
Schools entering a new 5-year E-Rate Category 2 cycle (FY2026-2030) with fresh budgets available.
How We Calculate It
Formula-based. We calculate each school's new Category 2 budget using the public formula: $167 per student, maximum $167,000 per school. We use NCES enrollment data to compute the budget. Both the source (NCES) and the formula (FCC rules) are public.
3.2 CEP Threshold Proximity
What We Identify
Schools within 2-5% of the 40% Community Eligibility Provision (CEP) threshold.
How We Calculate It
We use FRAC ISP (Identified Student Percentage) data plus enrollment to identify schools near the 40% threshold. Schools crossing 40% ISP unlock 100% free meals AND increase Title I eligibility. This is a directional signal — schools should verify their exact ISP with their state nutrition agency.
3.3 SAIPE Allocation Lag
What We Identify
Schools in high-growth poverty corridors likely to receive Title I allocation increases when Census data catches up.
How We Calculate It
Census SAIPE data has an 18-month lag. Current Title I allocations may be undercounting recent demographic shifts. We identify schools in high-growth poverty corridors (using enrollment trends, locale changes, and historical SAIPE patterns) that are likely to receive allocation increases when the next SAIPE release updates. This is a directional signal — not a guarantee.
3.4 Undercounting Gaps
What We Identify
Schools with low direct certification rates relative to FRL applications — potential gaps in student eligibility identification.
How We Calculate It
We compare public USDA direct certification rates (by state) against FRL application rates. Schools with significant gaps may be missing eligible students. We flag these for self-audit — schools can use our calculators to verify their numbers. This is a directional signal that requires school input to confirm.
4. What We Don't Have
We are explicit about what requires school input. We cannot and do not have access to:
- Direct certification match counts: Only the school has this data. We use public aggregate rates by state, but individual school match counts are not public.
- Current-year household income data: Only FRL applications have this. We use historical SAIPE estimates, but current-year income data is not public.
- SNAP/TANF/Medicaid individual student records: Legally restricted to program administration. We only use aggregate eligibility rates from public USDA reports — never individual records.
- Internal budget documents: School and district internal budgets are not public. We use federal allocation data and public board minutes, but internal budget planning is not available.
Why We Offer Self-Service Calculators
This is why we offer self-service calculators — enter your numbers, we crunch them. We never store the results. All calculations happen client-side in your browser. Sensitive inputs never leave your device.
5. School Privacy + Data Use
ThinkKits is built on public data. Here's what that means for privacy:
- All data on schools is public record: School names, addresses, enrollment, demographics, Title I status, E-Rate filings — all of this is already public via NCES, USAC, and other federal sources.
- We do not store individual student data: We never have access to student names, IDs, or individual records. All our data is school- or district-level aggregates.
- Client-side calculators process sensitive inputs in the browser only: When you use our calculators (direct certification, CEP ISP, etc.), your inputs are processed entirely in your browser. Nothing is transmitted to our servers. We never store the results.
- SNAP/TANF/Medicaid individual data is NEVER used: We only use aggregate eligibility rates from public USDA reports. We do not and cannot access individual student SNAP, TANF, or Medicaid records — those are legally restricted to program administration.
For full details, see our Privacy Policy and Data Processing Agreement (DPA).
6. Vendor Transparency
Vendors see funding SIGNALS, not confirmed facts. Here's what that means:
- Every signal has a confidence label: Verified / Estimated / Directional. Vendors can see exactly how certain we are about each signal.
- Board minutes data comes from public LEA meeting records: We scrape public board portals (BoardDocs, Simbli) and state public records systems. This is all public information — we just aggregate it.
- We do not resell student data: We don't have student data to resell. All our data is school- or district-level aggregates from public sources.
- Vendor intelligence is a transparent byproduct of our school discovery mission: We help schools find funding. When we surface a school with an active E-Rate Category 2 budget, that's useful to vendors too. But it's all built on public data — no secret intelligence.
For Vendors: Verify Before Acting
All signals are inferences from public data. Always verify with the school before making purchasing decisions. We provide signals to help you prioritize outreach — not to replace due diligence.
7. How Schools Can Verify
Every data point in ThinkKits is traceable to its source. Here's how schools can verify our data:
- Every data point links to its source: Click any data point in your school profile to see the source URL and original record.
- Schools can challenge incorrect data via our dispute form: If you find an error, use our dispute form to report it. We investigate and update within 48 hours.
- We update data as new sources release: Automated scripts download the latest releases from each source within 48 hours of publication.
- NCES updates: August each year (typically reflects prior school year).
- USAC updates: Quarterly filing windows (E-Rate commitments, Category 2 budgets).
For a complete update schedule, see our Data Source Catalog.
8. A Note About Our Confidence System
Every funding signal in ThinkKits is labeled with one of three confidence tiers. This tells you exactly how certain we are:
VERIFIED
Direct public record confirms this. Example: School filed E-Rate Form 470 (visible in USAC database).
ESTIMATED
Calculated from public formula. Directionally accurate, but verify exact numbers. Example: C2 budget = $167 × enrollment.
DIRECTIONAL
Pattern-based signal. Research before acting. Example: SAIPE lag forecast for high-growth poverty corridors.
Why This Matters
We never want schools or vendors to act on signals without understanding the confidence level. A VERIFIED signal means you can act with confidence. An ESTIMATED signal means you should verify the exact numbers. A DIRECTIONAL signal means you should do additional research before making decisions.