Healthcare fraud intelligence built to surface exclusion-linked control risk.
SentinelGraph helps qualified professionals identify exclusion-linked control risk using structured public-source intelligence, entity-resolution methods, and evidence-traceable reporting designed to support professional review.
Public-source intelligence. Human-reviewed findings. Evidence-traceable reporting.
22M+
entities tracked
209,000+
active leads
26,000+
critical-priority
5,500+
gold stars validated
21
data sources
What We Do
Structured intelligence for exclusion-linked risk
SentinelGraph maps the relationships between excluded individuals, healthcare entities, and the control structures that connect them using publicly available records.
The platform is designed to help qualified professionals identify patterns that are difficult to detect through standard screening alone: active control roles, post-exclusion enrollment, cross-entity linkage, and reimbursement-linked risk.
Entity & Control Mapping
We identify the corporate structures, officer roles, registered agents, and operational patterns that may indicate ongoing control by excluded individuals — even when that control is not immediately visible.
Exclusion Cross-Referencing
Every entity and individual in the graph is cross-referenced against OIG-LEIE, SAM.gov, state Medicaid exclusion lists, and related federal and state enforcement actions.
Evidence-Traceable Findings
Every observation is linked to a specific public record, filing, or data source. Nothing is inferred without attribution. Nothing is presented without a chain of evidence.
Review-Grade Reporting
Outputs are designed for use by attorneys, investigators, and compliance officers. Structured findings, not raw data. Confidence-rated, not speculative.
Court & News Validation
Every critical lead is cross-referenced against federal court records and news coverage to identify cases already under prosecution or public scrutiny — validating our findings and identifying net-new discoveries.
Continuous Intelligence Cycle
The platform refreshes daily — ingesting new data, rescoring leads, and cross-referencing against courts and news. This is a living intelligence engine, not a static report.
Sample Dossier
What an investigator-ready report looks like
Below is a redacted preview of a real Investigation Memo. Sensitive fields are masked, but the structure, evidence chain, and depth are exactly what subscribers receive.
Every dossier includes
- ✓Personalized header
Subscriber name, report ID, generation timestamp — every report watermarked
- ✓Subject profile + risk score
Full identity, NPI, state, scoring breakdown
- ✓Narrative analysis
Plain-English explanation of what the data shows
- ✓Proof ladder
Step-by-step evidence checklist with confirmed and pending items
- ✓Open questions
Unverified elements that warrant further analyst review
- ✓Recommended next step
Structured path for deeper review, escalation, or referral
Want to try it yourself? Browse our live sample data — over 1,000 real masked leads from the intelligence graph. Click any row to generate a sample report in any of our four formats.
Explore the live sample dataCONFIDENTIAL MATTER SUMMARY
CLASSIFICATION: PRELIMINARY
Investigation Memo
Subject
Em****ld Med****l C****r LLC
NPI ******4821 · FL · corporate_sanction_match
Narrative
Subject Em****ld Med****l C****r LLC (NPI ******4821) was identified through cross-referencing the █████████ exclusion list against active Medicare enrollment data maintained by █████████. The match was established using corporate name exact with a confidence level sufficient for human review.
The subject is registered in FL and currently holds an active operational status despite the exclusion. ████████████████████████ indicating that billing activity may continue despite the sanction. Federal court records confirm a related case filed in █████████ District Court on █████████.
Proof ladder
Open questions
- Full ownership chain through state corporate filings: █████████
- Related entities at the same registered address: █████████
- Historical enrollment changes and effective dates: █████████
Subscribe to see all identifier information and remove redacted data
Sample report with sensitive fields masked (shown as █). Subscribers receive fully unredacted versions with complete evidence chains.
Investigation Memo (Tier 2) — one of four report formats available
Why It Matters
Exclusion-linked control is difficult to detect — and easy to miss
Hidden in plain sight
Excluded individuals frequently maintain influence over healthcare entities through family members, business associates, or layered corporate structures. Standard screening tools check names — not control relationships.
Costly when missed
When excluded individuals continue to control billing entities, the resulting claims may be considered false under the False Claims Act. Liability can extend to payers, contractors, and downstream providers who failed to detect the risk.
Difficult to assemble manually
Tracing control through corporate filings, licensing boards, property records, and enforcement histories across multiple states is time-consuming and error-prone. SentinelGraph automates the assembly; human analysts validate the findings.
Process
How SentinelGraph works
SentinelGraph turns fragmented public records into structured, reviewable intelligence.
Data foundation
We ingest and structure public records — exclusion lists, corporate filings, licensing data, enforcement actions, court records, and property filings — into a unified entity graph.
Entity resolution
Individuals and organizations are resolved across data sources using name, address, license number, and corporate role matching — producing a single view of each actor and entity.
Control mapping
We map the relationships between excluded individuals and active healthcare entities — identifying officer roles, registered agent connections, address overlaps, and other indicators of potential control.
Review and reporting
Every finding is reviewed by a human analyst before delivery. Outputs include confidence ratings, evidence citations, and structured recommendations for follow-up.
Continuous validation
Critical leads are cross-referenced daily against federal court records and news coverage. Leads confirmed by public prosecution or reporting become validated catches — proving the system's accuracy.
Why SentinelGraph
What makes this different
Control-focused, not just name-based
Most exclusion screening checks names against a list. SentinelGraph maps the corporate and relational structures that indicate whether an excluded individual may still exercise control.
Evidence-traceable, not black-box
Every finding links directly to a public source document. Nothing is inferred without attribution. This makes outputs reviewable, defensible, and suitable for legal or compliance use.
Built for professional workflows
Outputs are structured for use in investigations, compliance audits, and legal briefings — not as raw data feeds. We deliver review-grade findings, not dashboards.
Public-source by design
SentinelGraph works exclusively with publicly available records. This means our methodology is transparent, our findings are independently verifiable, and our process does not depend on proprietary or privileged data sources.
Example Matters
The kinds of patterns SentinelGraph surfaces
These are representative composites based on commonly observed patterns. They illustrate the types of findings SentinelGraph produces — not specific investigations. No real individuals or entities are described.
Corporate shell layering
An excluded individual is removed as an officer from a healthcare entity. Within months, a new LLC is formed at the same address, with a family member listed as the registered agent. The new entity begins billing Medicaid.
Cross-state reconstitution
A provider excluded in one state appears as a controlling officer of a newly formed entity in another state, using a slightly different name variant. The new entity applies for Medicaid enrollment.
Address and role clustering
Multiple healthcare entities share a registered address, phone number, or officer with an entity previously linked to an excluded individual. Billing patterns overlap in ways that may suggest coordinated control.
Who We Serve
Built for professionals who need structured signal, not noise
Healthcare Fraud Attorneys
Counsel pursuing or defending False Claims Act cases, qui tam actions, or exclusion-related matters. SentinelGraph provides structured control-mapping intelligence to support case development and risk assessment.
Federal & State Investigators
OIG, DOJ, state AG, and MFCU investigators working exclusion-related or program-integrity cases. SentinelGraph accelerates identification of control patterns that may warrant further investigation.
Compliance Officers
Healthcare organizations, managed care plans, and PBMs responsible for ensuring their provider networks do not include entities controlled by excluded individuals. SentinelGraph provides deeper screening than standard name-match tools.
Program-Integrity Stakeholders
State Medicaid agencies, Medicare contractors, and other payer-side integrity teams. SentinelGraph supports proactive risk identification across provider enrollment and network adequacy workflows.
Methodology
How trust and proof are established
Every SentinelGraph finding is built on a layered framework of evidence quality, source reliability, and confidence assessment.
The goal is not simply to detect a pattern, but to show what is known, what remains uncertain, and what should happen next.
Every finding is presented with source context, confidence framing, and unresolved questions. SentinelGraph does not make determinations of fraud, liability, or regulatory violation.
National Coverage
Public-source intelligence across all 50 states
SentinelGraph structures public-source healthcare, enrollment, sanction, and corporate records across the United States into actionable intelligence.
SentinelGraph monitors exclusion-linked control risk across all 50 states, with deep coverage in high-activity regions.
Geographic visualization reflects public-source data coverage. It is not a determination of fraud concentration or prevalence.
22M+
entities tracked
209,000+
active leads
26,000+
critical-priority
5,500+
gold stars validated
21
public-source datasets
50
states with active coverage
Request a confidential briefing
If you work in healthcare compliance, fraud investigation, legal oversight, or program integrity — and want to understand how SentinelGraph approaches exclusion-linked control risk — we would welcome a confidential conversation.
What SentinelGraph is not
Not a law firm or legal advisor
Not a determination of fraud, liability, or regulatory violation
Not a substitute for investigation or legal judgment
Not a consumer screening tool
Not a replacement for qualified professional review
SentinelGraph is an intelligence and review-support platform built from public-source records and other lawful-source materials. All findings are preliminary, evidence-traceable observations. Independent professional review is always required.
Important 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.