Industries / Insurance

AI for Insurance

The Claim Is Only as Good as the Evidence Behind It

Photos, dash and body footage, recorded statements, estimates, and proof-of-loss documents arrive per claim and rarely in one format. VIDIZMO organizes that evidence by claim, lets adjusters and SIU teams question it, and redacts personal, health, and card data before anything is shared with a third party.

RISK SURFACE3 FLAGS

LOAN FILE

RECORDED CALL

card number muted · 00:42–00:51

Signature mismatchp.3 vs p.7
Reused documentseen in 2 applications
Amounts inconsistentconfidence 0.86
flagged before funding · audit trail attached

Trusted where the stakes are high

ExxonMobilJohn CockerillHartfordDavisPolkCleary GottliebWhite & CaseDepartment Of StateDMV CaliforniaMissouriMolina HealthcareEl Dorado Community Health CentersMemorial Sloan Kettering Cancer CenterFarmers & Merchants BankCapitaHaidar Capital ManagementKAPSARCOman LNG-2Saudi WaterU MassOklahoma University College of Medicine

What We've Done

Work, not slideware

The Hartford

Claimants submit photos and video of loss through a unique upload link per claim, and the SIU team finds any submission again through metadata tagging and search rather than hunting through a shared drive. The same library holds the unit's fraud-detection training.

EnterpriseTubeSIUPer-claim upload links

Reserv

Claims documents, checks, ACH forms, and statements redacted automatically in a claims-folder pipeline, with rules tuned to the carrier's own data formats.

RedactorClaims pipelineFinancial PII

Why VIDIZMO

We speak claim file, adjuster, and SIU

Claims run on evidence that arrives in every format and has to be shared without leaking the policyholder. Digitized claims mean more multimedia per file, SIU teams need to spot patterns across claims rather than inside one, and anything sent to a subrogation partner, an independent adjuster, or a regulator has to shed personal, health, and card data first. The products work inside those constraints: claim-folder-centric evidence with retention and audit trails, AI that reads recorded statements and estimates, and bulk redaction tuned to your own document formats, deployed inside your security boundary and never training on your data.

PII, PCI and PHI redactionHIPAA for health claimsState insurance regulationsSOC 2Audit trail on every actionNever trains on your data

FAQ

AI for insurance, asked and answered

What does VIDIZMO do for insurance carriers?

Organizes claims evidence by claim, so photos, footage, recorded statements, estimates, and proof-of-loss documents live in one record with retention and an audit trail. AI reads that evidence so adjusters and SIU teams can question it, and bulk redaction strips personal, health, and card data before anything is shared outside.

How does it help a special investigations unit?

SIU teams get evidence they can actually search: metadata tagging and AI search across submissions, transcription and summarization of recorded statements, and analysis that looks across claims rather than inside a single file. Claimants can submit evidence directly through a unique upload link per claim.

Can it redact policyholder data before we share evidence?

Yes. Faces, plates, names, addresses, account and card numbers, and health identifiers are detected and redacted across video, audio, images, and documents, including scanned records via OCR. Rules can be tuned to your own document formats, which is how carriers handle claim numbers and account formats specific to their systems.

Which regulations does this support?

Redaction and audit trails support HIPAA where claims involve health information, PCI-DSS where card data appears, and state privacy laws including CCPA. The platform itself is SOC 2 audited. State insurance regulations on claims handling and recordkeeping are supported through retention scheduling and chain of custody.

Does our claims data train anyone's AI models?

No. VIDIZMO deploys in your cloud or on-premises and your data is never used to train AI models.

Bring one claim folder

A total-loss file, a stack of recorded statements, a batch of estimates. We will show you what the AI reads and what it redacts, on your infrastructure.