Autonomous fraud detection and SIU-ready packets.
Layerup agents continuously monitor intake, documents, and emerging file evidence for fraud signals, build entity networks across the book, and assemble investigator-ready referral packets inside your existing systems.
From signal to substantiated outcome.
Layerup runs continuously across intake, file development, and book-level patterns — and feeds outcomes back into the signal engine.
- 01Continuous signal monitoring
- 02Cross-file pattern detection
- 03Evidence assembly
- 04Referral packet
- 05SIU investigator handoff
- 06Outcome tracking
Seven workflows. One detection model.
Each workflow is a deployable agent surface — start with intake-time signals or cross-file network detection, and expand into investigator workbench support.
Catch fraud where it starts — at intake.
Agents evaluate every new claim at intake — coverage, parties, mechanism, prior history, and supporting documentation — and surface high-confidence fraud signals before the file is assigned.
- 01Coverage and party reconciliation at intake
- 02Mechanism-of-loss consistency review
- 03Prior loss and prior carrier history
- 04Channel and contact anomaly detection
- 05Severity-weighted signal scoring
Statements, documents, and the timeline — all in agreement.
Agents continuously compare insured and witness statements, supporting documents, photos, repair estimates, and timeline events for inconsistencies that warrant a closer look.
- 01Statement-to-statement comparison
- 02Statement-to-document comparison
- 03Photo and metadata review
- 04Repair / medical / damage consistency
- 05Timeline contradiction flags
Surface repeat actors before they cost you.
Agents identify repeat providers, vendors, claimants, attorneys, and counterparties across the book and flag patterns that warrant SIU review.
- 01Provider and vendor repeat detection
- 02Attorney and representative patterns
- 03Body shop and DRP outlier patterns
- 04Cross-claim claimant linkage
- 05Geographic and temporal clustering
Networks visible at the book level, not the file level.
Agents build entity and relationship graphs across the entire claims book and surface emerging fraud networks the file-level view can never see.
- 01Entity resolution across the book
- 02Relationship and network construction
- 03Cluster and ring detection
- 04Severity and exposure roll-up
- 05Network-level alerts for SIU
Referral packets investigators can actually use.
Agents synthesize signals, evidence, and history into a complete, investigator-ready referral packet — citations, exhibits, timeline, and rationale included.
- 01Signal and evidence synthesis
- 02Exhibit assembly with citations
- 03Timeline construction
- 04Rationale documentation
- 05Routing to the right SIU desk
Continuous support throughout the investigation.
Once a file is in SIU, agents continue ingesting new evidence, summarizing developments, drafting subject interview prep, and assembling supplemental exhibits on demand.
- 01Continuous evidence ingestion
- 02Investigation summary updates
- 03Subject interview prep packets
- 04Supplemental exhibit assembly
- 05Database and external source lookups
Every outcome becomes signal.
Substantiated, unsubstantiated, and inconclusive outcomes feed back into the signal engine so detection precision improves over time.
- 01Outcome capture per referral
- 02Precision and recall reporting
- 03Signal tuning by LOB and pattern
- 04False positive review loop
- 05Executive-grade fraud reporting
Move fraud and SIU work from doing to approving.
Start with one signal class or one LOB. Prove the detection lift and SIU packet acceptance rate, then expand book-wide.