Federal program fraud analytics across 278+ datasets. Cross-referenced, name-standardized, and query-ready.
PPP, Medicare, SNAP, federal contracts, SEC filings, EPA enforcement, CFTC actions, provider exclusions, sanctions lists, and more — linked by standardized entity matching across 806 normalized columns.
Every entity name and address is normalized across all 278+ tables — lowercase, trimmed, special characters stripped. This means "ACME HEALTH LLC", "Acme Health, L.L.C.", and "acme health llc" all resolve to the same entity. 806 standardized columns enable cross-database joins that would take weeks to build from raw data.
A 41M-row master entity table resolves entities across all 278+ datasets — linking PPP borrowers to sanctions lists, enforcement actions, SEC filings, EPA violations, federal contracts, relief fund payments, and state registrations. Connections that take analysts days to find are already materialized and queryable.
Federal contracts (25.9M rows), pandemic relief programs (6.1M PPP + 9M EIDL loans, 420K Provider Relief Fund payments), SBA 7(a)/504 loans (2.1M), Medicare/Medicaid (286M+ claims), SEC EDGAR filings (8.2M), CFPB complaints (14M), EPA ECHO, SNAP retailers, state business registrations (11 states), and global sanctions — all in one queryable warehouse.
Ask questions in plain English. "Which federal contractors also appear on global sanctions lists?" translates to SQL automatically and runs against the full database. Pro and Enterprise tiers.
$0
$20/mo
$200/mo
Lending & Relief
PPP Loans (6.1M)
EIDL Loans & Advances (9M)
SBA 7(a) Loans (1.9M)
SBA 504 Loans (224K)
Provider Relief Fund (420K)
USAspending Grants (9M)
Healthcare
Medicare Claims (59M)
Medicaid Claims (227M)
Part D Prescribers (154M)
NPPES Providers (9.4M)
Open Payments (82M)
SEC & Financial
EDGAR Filings (8.2M)
Insider Transactions (12M)
13F Holdings (87M)
CFTC Enforcement
FDIC Call Reports (4.7K)
Sanctions & Exclusions
OpenSanctions (1.5M)
LEIE (83K)
OFAC SDN (19K)
Consolidated Screening (25K)
World Bank Debarment
Regulatory & Contracts
Federal Contracts (25.9M)
EPA ECHO (3.1M)
FDA Enforcement (69K)
FMCSA Carriers (4.4M)
CFPB Complaints (14M)
Entity Registry & Other
Master Entity Table (41M)
State SOS Filings (11 states)
IRS Exempt Orgs (1.9M)
SNAP Retailers (703K)
HUD Section 8 (24K)
The fastest way to get started. Works with any AI agent or terminal.
# Install
pip install fraudgraph
# Authenticate
export FRAUDGRAPH_API_KEY=your_key_here
# Check connection
fraudgraph health
# List available tables
fraudgraph catalog
# Run a SQL query
fraudgraph query "SELECT BorrowerName, CurrentApprovalAmount FROM ppp ORDER BY CurrentApprovalAmount DESC LIMIT 10"
# Ask in plain English (Pro/Enterprise)
fraudgraph ai "Which Provider Relief Fund recipients are also excluded from Medicare?"
# Download PPP dataset as Parquet
fraudgraph download ppp
from fraudgraph import FraudGraph
fg = FraudGraph(api_key="your_key_here")
# Run a query
result = fg.query("SELECT * FROM ppp LIMIT 10")
# Ask in plain English
result = fg.ai("Which federal contractors are on sanctions lists?")
# Browse tables
tables = fg.catalog()
Use curl or any HTTP client. All endpoints accept and return JSON.
# Check API status
curl https://api.k3analytics.io/health
# Browse available tables
curl -H "X-API-Key: YOUR_KEY" https://api.k3analytics.io/v1/catalog
# Find PPP borrowers on sanctions lists
curl -X POST -H "X-API-Key: YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"sql":"SELECT p.BorrowerName, p.CurrentApprovalAmount, o.caption FROM ppp p JOIN opensanctions o ON p.std_org_name = o.std_org_name LIMIT 10"}' \
https://api.k3analytics.io/v1/query
# AI query (Pro/Enterprise)
curl -X POST -H "X-API-Key: YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"question":"Which Provider Relief Fund recipients are also excluded from Medicare?"}' \
https://api.k3analytics.io/v1/ai/query
K3 Analytics · @K3_Analytics