$2.96T in federal grant obligations surveyed, 66 concentration findings surfaced from USAspending.gov.
grants-engine ingested 1,000 federal awards (assistance types 02-05, calendar year 2024) from USAspending.gov public data, covering 321 distinct recipients across 16 federal agencies. Tier 1 ran a single deterministic pass against the recipient-concentration check and produced 66 findings (39 critical, 27 high). California's Department of Health Care Services holds 21.36% of all HHS grant obligations across the surveyed window ($511.7B). Amtrak holds 39.33% of all DOT grant obligations ($36.1B). Real federal data, real findings, replayable with the published code version and the same source register.
What this POC shows.
If you're a federal grants compliance officer, a state GMO, or an HHS-OIG / DOJ recovery analyst, this is the short answer for what's being detected on USAspending.gov data.
What's the dataset?
USAspending.gov federal grants register. $2.96T in obligations surveyed. Public, free, deterministic. Same data the Treasury Office of the Inspector General has.
What did JIL find?
66 concentration findings: recipient-level over-concentration (single recipient capturing disproportionate grant flow within an agency program), program-overlap patterns, sole-source frequency anomalies. Each finding tied to the USAspending row(s) that fired the rule.
Why does this matter?
Federal grants fraud is the #2 source of FCA recoveries after healthcare. The data is public, but nobody runs systematic outlier detection at scale. JIL does, with deterministic rules and admissible evidence.
What this is NOT
Not an FCA determination. Not a referral. 'Flagged' = 'public obligations data shows a pattern worth review.' The qui tam / agency referral decision stays with the analyst or relator's counsel.
How do I run this on my book?
If you're an agency GMO or an OIG analyst, we run the universal catalog plus your agency-specific rules. Turnaround typically 7-10 days for a multi-year program review.
USAspending.gov, real federal grant data.
Source. The U.S. Treasury publishes every federal award through USAspending.gov, the federally-mandated public reporting system for federal spending. The search API exposes assistance award types 02 (block grant), 03 (formula grant), 04 (project grant), and 05 (cooperative agreement) at api.usaspending.gov/api/v2/search/spending_by_award/. No authentication required, full query coverage, cited as the authoritative federal record.
What we ingested. 10 pages of 100 awards each, sorted by Award Amount descending, time period January 1 to December 31 2024. Loaded into grants.federal_awards with content-addressable hashes for replay.
What is concentration. A (awarding_agency, recipient_uei) pair is flagged when one recipient receives more than the configured percentage of an agency's total obligations across all surveyed recipients AND exceeds the configured dollar floor. Defaults: 5 percent share, $5,000,000 floor. Severity scales with both share and absolute dollar exposure.
Why this matters. 2 CFR 200 (Uniform Guidance) imposes competition, cost-allowability, and single-audit requirements that scale with both the size of the award and the size of the recipient relative to the agency's grant pool. OMB Circular A-133 routes recipients above defined thresholds into the cognizant agency for single-audit oversight. GAO Yellow Book applies. The public register is the single common reference point for inspectors general, oversight committees, and recipients themselves.
Top of the concentration list, sorted by total agency obligation.
Each row below ran gr_recipient_concentration (Recipient Concentration Risk) against the live ingested federal awards. Severity threshold: critical at 50 percent share OR $1B+, high at 20 percent OR $100M+, medium at 10 percent OR $25M+. The top of the list is dominated by state Medicaid administrators and large transit / emergency-management entities; one large defense-research consortium appears at #24.
| # | Recipient | Awarding Agency | Share | Total obligation | Awards | Tier 1 signals |
|---|---|---|---|---|---|---|
| 1 | CA Health Care Services | HHS | 21.36% | $511,706,412,484 | 13 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL MEDICAID-BLOCK |
| 2 | NYS Department of Health | HHS | 10.23% | $245,142,978,462 | 10 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL MEDICAID-BLOCK |
| 3 | Governor's Authorized Representative | DHS | 19.04% | $39,118,357,326 | 5 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL DISASTER-RELIEF |
| 4 | National Railroad Passenger Corp (Amtrak) | DOT | 39.33% | $36,084,922,117 | 12 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL DEDICATED-RECIPIENT |
| 5 | NYS Homeland Security & Emergency Services | DHS | 16.39% | $33,681,467,747 | 5 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL DISASTER-RELIEF |
| 6 | Government of the Virgin Islands | DHS | 10.70% | $21,984,671,341 | 1 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL SINGLE-AWARD |
| 7 | CA Department of Education | USDA | 16.30% | $19,505,444,925 | 10 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL SCHOOL-NUTRITION |
| 8 | CA Office of Emergency Services | DHS | 9.39% | $19,299,534,343 | 7 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL DISASTER-RELIEF |
| 9 | Metropolitan Transportation Authority | DOT | 20.49% | $18,802,241,437 | 10 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL TRANSIT |
| 10 | TX Department of Agriculture | USDA | 14.11% | $16,889,133,594 | 8 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL SCHOOL-NUTRITION |
| 11 | FL Division of Emergency Management | DHS | 7.31% | $15,027,957,775 | 9 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL DISASTER-RELIEF |
| 12 | TX Division of Emergency Management | DHS | 7.03% | $14,444,005,166 | 2 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL DISASTER-RELIEF |
| 13 | PR Homeland Security & Emergency | DHS | 6.19% | $12,726,652,837 | 6 | CONCENTRATION-CRITICAL DOLLAR-CRITICAL DISASTER-RELIEF |
| 14 | CA Department of Social Services | USDA | 7.78% | $9,316,574,577 | 11 | CONCENTRATION-CRITICAL DOLLAR-HIGH SNAP |
| 15 | TX Education Agency | Education | 17.80% | $8,498,930,217 | 6 | CONCENTRATION-CRITICAL DOLLAR-HIGH TITLE-I |
| 16 | NYS Education Department | USDA | 5.90% | $7,063,410,086 | 7 | CONCENTRATION-CRITICAL DOLLAR-HIGH SCHOOL-NUTRITION |
| 17 | CA Department of Education | Education | 14.77% | $7,051,015,763 | 4 | CONCENTRATION-CRITICAL DOLLAR-HIGH TITLE-I |
| 18 | Climate United Fund | EPA | 28.94% | $6,970,000,000 | 1 | CONCENTRATION-CRITICAL DOLLAR-HIGH GGRF |
| 19 | NYS Education Department | Education | 13.55% | $6,471,615,370 | 6 | CONCENTRATION-CRITICAL DOLLAR-HIGH TITLE-I |
| 20 | FL Department of Agriculture | USDA | 5.03% | $6,019,787,140 | 5 | CONCENTRATION-CRITICAL DOLLAR-HIGH SCHOOL-NUTRITION |
| 21 | New Jersey Transit Corp | DOT | 6.17% | $5,665,981,229 | 7 | CONCENTRATION-CRITICAL DOLLAR-HIGH TRANSIT |
| 22 | Coalition for Green Capital | EPA | 20.76% | $5,000,000,000 | 1 | CONCENTRATION-CRITICAL DOLLAR-HIGH GGRF |
| 23 | IL State Board of Education | Education | 7.83% | $3,737,730,254 | 6 | CONCENTRATION-CRITICAL DOLLAR-HIGH TITLE-I |
| 24 | National Center for Manufacturing Sciences | DoD | 43.74% | $3,386,262,787 | 3 | CONCENTRATION-CRITICAL DOLLAR-HIGH RESEARCH-CONSORTIUM |
| 25 | TX Comptroller of Public Accounts | Commerce | 8.97% | $3,312,616,455 | 1 | CONCENTRATION-CRITICAL DOLLAR-HIGH SINGLE-AWARD |
Where the dollars sit.
grants-engine produces a finding per (agency, recipient) pair that crosses the concentration threshold. Severity scales with both share percent and absolute obligation: critical at 50 percent share OR $1B+, high at 20 percent OR $100M+, medium at 10 percent OR $25M+, low otherwise. The 66 findings ingested across 16 federal agencies surface every meaningful concentration in the top-1000 awards population.
50 percent share OR $1B+ obligation.
Headlines: CA Health Care Services 21.36% / $511.7B (HHS), NYS DOH 10.23% / $245.1B (HHS), GAR 19.04% / $39.1B (DHS), Amtrak 39.33% / $36.1B (DOT). State Medicaid + disaster-relief cohort dominates.
20 percent OR $100M+ exposure.
State education agencies (TX TEA, IL ISBE), state agriculture departments (TX TDA, FL FDACS), regional transit (NJ Transit, MTA), GGRF awardees (Climate United, Coalition for Green Capital).
Below threshold.
The dollar floor at $5M and the share floor at 5% kept the long tail out of the run. Lowering the floor surfaces an additional ~200 findings at the medium / low tier; the engine caps to top 500 in any single pass.
What ships when an OIG / IG-staff buyer engages.
Recipient concentration is one signal of three. grants-engine ships two additional production checks gated on the customer profile lob = 'federal_grants_oversight'. Each check runs deterministically against USAspending.gov public data and / or customer-supplied contract modification records, and produces sealed CREB™ output through the same orchestrator and Ava layer that powers the rest of the platform.
Outsized recipient share.
Single recipient holds an outsized share of an agency's grant pool. Pattern signal for sole-source awards that should have been competed, capture relationships, or pass-through structures. 2 CFR 200, GAO Yellow Book, OMB Circular A-133.
Self-subcontracting.
Identical recipient_uei appears as both prime award holder and parent award holder across distinct awards. Pattern signal for self-subcontracting, layered intermediaries, or administrative-fee skimming on a chain the recipient controls. 2 CFR 200, False Claims Act 31 USC 3729.
Performance period or scope overrun.
action_date past period_of_performance_end OR total_obligation materially exceeds the sum of federal_action_obligation across siblings sharing the same prime_award_id. Pattern signal for unrecorded modifications or scope expansion outside competition. 2 CFR 200.308, FAR 43, OMB A-11.
What the OIG takes to a single-audit referral.
One of the 39 critical findings, rendered as a sealed CREB™ record. The bundle carries the cryptographic finding hash, the exact reproducibility manifest, and the regulatory-basis citations.
finding_id : 83736d25-7fbf-4cdd-9a06-37130939fca0 check_id : gr_recipient_concentration subject_type : agency_recipient_pair subject_id : Department of Health and Human Services|JE73CDQUAPA7 recipient_name : HEALTH CARE SERVICES, CALIFORNIA DEPARTMENT OF recipient_uei : JE73CDQUAPA7 awarding_agency : Department of Health and Human Services severity : critical recipient_obligation : $511,706,412,484 agency_total_obligation : $2,395,322,650,000 share_pct : 21.3611% award_count : 13 awards in surveyed window source : USAspending.gov public data (search/spending_by_award) regulatory_basis : 2 CFR 200 (Uniform Guidance), GAO Yellow Book, OMB Circular A-133 code_version : grants-engine@2026.05.01-grants-1 model_version : grants-v1 replay_command : jil-attest replay --bundle GFI-CONCENTRATION-2026-05-01-A001
Deterministic, reproducible, court-defensible.
SQL aggregate over public data.
The check is a SQL aggregate over a public federal dataset. Same input register (USAspending.gov), same threshold parameters, same (awarding_agency, recipient_uei) cohort, every run.
Rule-based verdict path.
The Tier 1 verdict path is rule-based. Ava (next layer) groups, narrates, and routes; it never produces the underlying flag. JIL operates the in-house LLM directly on customer-controlled hardware. No OpenAI, Anthropic, or Vertex API.
Bit-identical replay.
Every CREB™ carries the source-dataset hash, code version, query parameters, and signal thresholds. A third party with the same inputs replays the analysis bit-identically and lands on the same finding set.
One kernel. Eight industries. This vertical runs on the same sovereign L1 + attestation network that ships the other 7. Kernel age: 18+ months. Adding a vertical: ~1 week. Competitor moat: build the kernel first.