Slow first review
Documents arrive in different formats and must be checked before an assessor can start.
AI FOR INSURANCE OPERATIONS
Reduce claims bottlenecks without losing control of decisions.
Insurers deal with diverse document formats, policy rules, claim exceptions and manual handoffs. IRAH designs governed systems that prepare complete, traceable review packs for authorised personnel.
IRAH / APPROACHPROBLEM → EVIDENCE → DECISION
OPERATIONAL PROBLEM01 / CONSTRAINT 02 / CONSTRAINT 03 / CONSTRAINT
Three areas where teams lose time or clarity.
Rule interpretation
A benefit or exclusion should link to the current policy wording, not an invented AI answer.
Review overload
Incomplete and suspicious claims need different escalation routes.
ILLUSTRATIVE SYSTEM DESIGN
A connected workflow, not isolated AI features.
01
INTAKE
Recognise documents and flag missing evidence
02
VALIDATE
Check mandatory fields, dates and policy context
03
ASSIST
Prepare an evidence-linked claim summary
04
APPROVE
Route exceptions and consequential decisions to authorised reviewers
HOW WE WOULD VALIDATE
Agree an evidence-based pilot first.
Measure extraction accuracy, exception recall, time per reviewed claim and incorrect automation actions on a controlled sample.
HONEST POSITIONINGProposed architecture
These examples illustrate solutions available for evaluation. They are not claims of an existing implementation, client contract or guaranteed percentage saving.