Auto.IES™
Prevent eligibility errors before they become federal financial exposure.
Auto.IES is the new AI/NLP-enabled automated eligibility quality assurance (QA) service from Public Consulting Group (PCG) designed to help agencies protect their budgets from the cost of SNAP and Medicaid eligibility errors. Auto.IES allows states to automate the QA of virtually 100% of eligibility determinations – before decisions are made – by instantly identifying potential accuracy and/or procedural errors and returning these issues back to the caseworker to adjudicate before they certify eligibility.
Why Traditional Eligibility QA is No Longer Enough
State HHS agencies are entering a new era of payment-accuracy accountability and program integrity. Traditional retrospective, sample-based QA methods that identify issues after eligibility decisions have already been made are no longer enough. With new requirements under H.R. 1, agencies need a way to automatically identify accuracy and procedural issues across the full caseload before determinations are finalized. Auto.IES automates this pre-certification visibility through earlier, more consistent case review and policy-aligned analysis on virtually 100% of cases.
Auto.IES is designed to augment—not replace—human judgment, with final decisions remaining under human and agency authority.
Learn how Auto.IES helps agencies address eligibility QA before findings become penalties.
Explore how Auto.IES’s configurable, automated, AI-assisted reviews give caseworkers and program leadership granular visibility into eligibility and procedural issues, documentation gaps, system calculation errors, and policy-application trends across the full caseload.
How Auto.IES Works
Transparent AI. Human-controlled decisions. Audit-ready results.
See how Auto.IES transforms eligibility review.
Explore the step-by-step process behind policy-aligned case analysis, transparent findings, and human-centered decision support.
Key Benefits
Reduce HR-1 financial risk
Identify eligibility issues before they contribute to SNAP error rate or Medicaid PERM exposure.
Review more cases earlier
Move beyond small QA samples to automated and configurable reviews of your entire caseload.
Improve policy consistency
Reduce inconsistent rule application across workers, offices, and programs.
Target training precisely
Identify and address recurring error patterns by screen, rule, office, or worker — not blanket retraining.
Realize trust and transparency
View every AI step and recommendation that is logged with policy citations.
Protect sensitive data
No data is sent to models over the internet. • No models are trained on agency data.
Where Auto.IES Helps Agencies Create Value
Auto.IES helps agencies strengthen eligibility QA accuracy by automating prospective reviews of virtually 100% of eligibility determinations, improving review consistency, identifying potential issues earlier, and supporting documentation for oversight and audit readiness.
- Automated reviews of virtually 100% of cases
- Prospective, rather than retroactive QA reviews
- Granular feedback on eligibility and procedural issues and training needs
- More consistent QA review across programs and teams
- Stronger policy citations and audit-ready documentation
- Better use of staff time and review capacity
- Dramatic reduction in federal penalties associated with eligibility errors
Learn how agencies implement and scale Auto.IES.
Explore deployment phases, implementation considerations, and best practices for adoption.
Trust, Security & Responsible AI
Designed for regulated HHS environments
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148 State Street 10th FloorBoston, Massachusetts 02109‑2589