AI-assisted FNOL intake
New claims captured fast from calls, forms, emails — with human verification.
AI-assisted claims processing — FNOL intake, document extraction, triage, fraud signals and QA — reviewed by trained claims specialists at every step.
AI is genuinely useful in claims — FNOL intake, document extraction, categorization, triage and anomaly detection. But claims decisions affect real money, coverage and customers, so every AI-assisted output still needs a trained claims specialist to review, correct and own it.
Opervics runs AI-assisted claims processing as a managed function — AI handles intake, extraction and triage; specialists review and own each step; reporting shows both speed gain and accuracy that keeps claims defensible.
New claims captured fast from calls, forms, emails — with human verification.
AI extracts key fields from claim documents — specialists verify before commit.
Claims categorized and routed — simple fast-tracked, complex escalated.
AI flags unusual patterns — SIU-specialists review before escalation.
Every AI-assisted decision reviewed — accuracy tracked per claim type.
Cycle time, accuracy, AI assist rate, escalation rate and backlog trend.
These are the same operational issues we see across clients — and the same ones our process is designed to remove.
Claim decisions committed with no trained specialist in the loop.
FNOL volume overwhelms staff — customers wait for first response.
Wrong fields, missed pages — rework delays claims.
Suspicious claims paid before patterns are noticed.
Simple and complex claims handled the same way — slow for simple, sloppy for complex.
Nobody knows how often AI is right or where it fails.
Every service inherits the same baseline security posture, then adds service-specific controls on top.
Access, change management, monitoring and incident response aligned to SOC 2.
PII handling, redaction and access controls defined with your team.
Every AI-assisted decision reviewed and logged by trained specialists.
Cycle time, accuracy, AI assist rate and escalation rate reported weekly.
No — AI assists with intake, extraction, triage and anomaly detection. Trained adjusters and claims specialists review and own every decision.
FNOL intake, document extraction, claim categorization, triage, fraud signals and status summarization.
Human-in-the-loop review, claim-type specific QA rules and audit-ready logs — nothing AI-assisted commits without a trained specialist.
Guidewire, Duck Creek, Salesforce Financial Services, custom claims platforms, document management and portals.
Cycle time, accuracy, AI assist rate, escalation rate and backlog trend — reported weekly.
Per claim, per FTE, or a monthly retainer — agreed upfront.
A short conversation is usually enough to scope the volume and propose a starting point.