AI Document Automation Pro™ for SNAP Payment Accuracy
Protect State SNAP Funding in the Era of Reconciliation
The recent reconciliation legislation, H.R. 1, the "One Big Beautiful Bill" (119th Congress, P.L. 119-21) has dramatically raised the stakes for states administering the Supplemental Nutrition Assistance Program (SNAP).
The Challenge
Starting in FY 2028, states whose combined payment error rate (overpayments + underpayments; payments to ineligible households count as overpayments for federal QC) exceeds federal thresholds must share the cost of SNAP benefits:
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< 6% error rate → no state cost share
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6-8% error rate → 5% state contribution
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8-10% error rate → 10% state contribution
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> 10% error rate → 15% state contribution
For states with large SNAP caseloads, even a single percentage point above the threshold can translate into tens of millions in lost federal reimbursement annually. Agencies already managing caseload growth, staffing shortages, and legacy systems now face an urgent mandate: reduce error rates or absorb major financial losses.
Our Solution:
AI Document Automation Pro™ for SNAP Payment Accuracy
Our solution transforms how states ingest, verify, and monitor SNAP case data. By automatically extracting and normalizing information from paystubs, income verification forms, change reports, and scanned PDFs/handwritten documents, we surface discrepancies before they reach federal Quality Control (QC) samples helping you keep error rates below the threshold.
How It Works
Automated Document Ingestion
Pull in structured, semi-structured, and unstructured case records, including paystubs, employment verification, notices of action, and third-party wage data.
Smart Data Extraction and Normalization
Convert diverse paystub formats into a consistent, auditable schema capturing gross pay, net pay, hours, deductions, and YTD totals.
Income Verification and Risk Flagging
Check calculations (gross vs. net, hours x rate, monthly/annualized projections) and flag inconsistencies likely to cause eligibility or payment errors.
Error Monitoring and QC
Go beyond document review: validate extracted values directly against state eligibility and case management systems, mirroring the steps human auditors use today. Automatically pre-screen cases, replicate QC checklists, and provide transparent evidence packs for staff to confirm or override.
Audit-Ready Reporting
Produce explainable outputs that support corrective action plans, federal audits, and internal program integrity reviews.
Why It Matters
Protect Federal Funding
Meet error-rate commitments under H.R. 1 (P.L. 119-21) and avoid escalating state cost-shares.
Strengthen Program Integrity
Ensure eligible households receive the right benefits while ineligible or miscalculated payments are caught early and proven with audit-ready evidence.
Amplify Your QC Workforce
Pre-fill checklists and deliver evidence packs so auditors focus on judgment, not document hunting.
Scale Beyond SNAP
Extend the same approach to TANF, Medicaid, CHIP, and housing assistance where compliance and payment accuracy drive funding.
Why Now
The reconciliation bill creates an imminent, expensive compliance risk for every state SNAP agency. Beginning in FY 2028, states that fail to control error rates will bear a growing share of program costs putting billions at risk.
AI Document Automation Pro™ for SNAP Payment Accuracy gives you a fast, practical path to compliance: automate verification, align with QC practices, reduce errors, and protect your funding without disrupting existing workflows.