ExceptionLayer

Claims intake

Turn intake into an exception queue.

ExceptionLayer prepares the routine work surrounding a new claim—documents, matching, extraction, validation, chronology and routing—while keeping consequential claims decisions with your team.

Map your intake workflow

Initial boundary

No autonomous coverage, liability, reserve, fraud, denial, settlement or payment decisions.

Before

  1. 01Email arrives
  2. 02Attachments opened manually
  3. 03Claim/policy identified
  4. 04Fields re-keyed
  5. 05Missing information discovered late
  6. 06Conflicts reconciled by staff
  7. 07Claim shell assembled
  8. 08Adjuster receives partially prepared file

With ExceptionLayer

  1. 01Submission received
  2. 02Documents classified
  3. 03Claim and policy matched
  4. 04Fields extracted with source evidence
  5. 05Required information validated
  6. 06Conflicts surfaced
  7. 07Chronology prepared
  8. 08Exceptions routed
  9. 09Human approves
  10. 10System of record updated where appropriate

Exception taxonomy

Exceptions should be explicit.

The exact exception taxonomy is configured around the workflow, customer procedures and systems involved.

01missing policy identifier
02insured mismatch
03claimant ambiguity
04duplicate FNOL
05inconsistent loss date
06incomplete required documentation
07document / claim mismatch
08unreadable attachment
09unsupported document type
10low-confidence extraction
11business-rule conflict
12system lookup failure

Source-grounded extraction

Every important field should have somewhere to point.

Structured output is more useful when reviewers can trace important values back to the document, page or source that produced them.

Evidence mapCLM-28471
Loss dateAug 14, 2026FNOL_28471.pdf · p.1Conflict
Policy no.PL-99142-Adeclarations.pdf · p.1Verified
InsuredMark CalderFNOL_28471.pdf · p.1Verified
IncidentWater damageadjuster-note.pdf · p.2Verified

Test against the work your team already knows.

Initial deployments should be evaluated against historical examples and controlled live work before authority expands.

field-level correctnessdocument classificationmissing-information detectionconflict detectionduplicate detectionrouting correctnesshuman correction rateexception ratetouch timereworkcycle time

Deployment FAQ

The questions that matter before production.

One queue. Measured.

Show us the queue everyone hates.

If your team repeatedly reads, checks, re-keys, reconciles or routes the same operational work before judgment can begin, we should probably look at it.

Map the workflow

We’ll start with the workflow and its economics—not a generic AI demo.