How It Works
From public records to review-grade intelligence
SentinelGraph transforms fragmented public data into structured, evidence-traceable findings about exclusion-linked control risk. Here is how the process works.
Data Foundation
SentinelGraph continuously ingests and structures publicly available records from across the healthcare regulatory and corporate landscape.
OIG-LEIE exclusion records and reinstatement data
SAM.gov entity exclusion and debarment records
State Medicaid exclusion and sanction lists
State corporate filings across federal and state public-record systems
State licensing board records (medical, nursing, pharmacy, allied health)
Federal and state court records and enforcement actions
Property records, UCC filings, and business registrations
Medicare and Medicaid provider enrollment data (NPPES, PECOS, state equivalents)
Entity & Control Mapping
Records are resolved into distinct entities — individuals, organizations, and addresses — and connected through observed relationships.
Name, address, and identifier matching across data sources
Corporate officer, registered agent, and director role mapping
Address clustering and shared-infrastructure detection
Temporal analysis of entity formation, dissolution, and reconstitution
Public-record relationship indicators, including shared surnames, officer overlap, and repeated entity associations
Cross-state entity tracking for multi-jurisdiction control patterns
Trust & Proof Framework
Every observation passes through a structured confidence assessment before it becomes a finding.
Source reliability rating (official government record vs. secondary source)
Cross-source corroboration (finding confirmed in multiple independent sources)
Temporal consistency (do the dates and sequences make sense?)
Entity resolution confidence (how certain is the identity match?)
Control indicator strength (direct role vs. indirect association)
Human analyst review and confidence rating before delivery
Review-Grade Outputs
SentinelGraph delivers structured findings designed for use by legal, investigative, and compliance professionals.
Entity profiles with full relationship mapping
Control-indicator summaries with confidence ratings
Evidence citations linked to specific public records
Timeline reconstructions showing entity formation and control transitions
Structured narratives designed to support legal briefing, compliance review, or investigative follow-up
Structured data exports for integration with case management systems
Important limitation
SentinelGraph identifies patterns that may indicate exclusion-linked control risk or related structural concern. It does not make determinations of fraud, liability, or regulatory violation. All findings are preliminary observations designed to support — not replace — qualified legal, investigative, or compliance review. The presence of a pattern does not establish wrongdoing. The appropriate response to any SentinelGraph finding is further investigation by qualified professionals.
Request a confidential briefing
If you work in healthcare compliance, fraud investigation, or legal oversight — and you want to understand how exclusion-linked control risk may affect entities in your portfolio — SentinelGraph may be able to help.
Request a BriefingImportant disclaimer: SentinelGraph provides structured intelligence based on publicly available data. It does not provide legal advice, conduct investigations, or make determinations of fraud, liability, or regulatory violation. All findings are preliminary, evidence-traceable observations intended to support — not replace — qualified legal, investigative, or compliance review. Use of this service does not create an attorney-client relationship or any professional engagement unless separately agreed in writing.