Semantic evidence for insurance
Claims narratives, underwriting files, and the structural complexity of Lloyd's syndicates, joined as evidence for AI and investigators alike.
Where the unstructured story finally counts
The highest-signal underwriting and SIU material often live outside structured core systems. KnowledgeHub absorbs those artefacts into ontology classes correlated with exposures, treaties, and customer records.
You keep fraud models proprietary; middleware supplies the factual mesh they stand on.
- Blend medical, legal correspondence, imagery metadata, and third-party enrichment
- Maintain portfolio-wide counterparty comprehension
- Expedite SIU dossiers without shadow copies of sensitive media
How underwriting and SIU functions unify claim narratives safely
High-signal underwriting memos and special-investigations files often bypass the core, not because the organisation is careless but because evidence arrives as narratives, scans, transcripts, correspondence, and third-party bundles.
Common pains where unstructured data and agents matter
First-notice narratives sit outside risk models
Emails and PDF first notices contain modifiers models never ingest. Retrieval-grounded extraction helps structure signals with citations rather than silent assumptions.
SIU dossiers are rebuilt manually per referral
Folder hunts recreate evidence each time supervisory or legal reviewers ask. Agents assemble draft timelines with passages linked, and SIU adjudicates authenticity.
Treaty and syndicate wording hide in unstructured riders
Collateral references live in unstructured endorsements annexes. Semantic clause search binds obligations to exposures with provenance instead of spreadsheet guesswork.
Outcomes organisations typically target
- Faster triage across structured and unstructured records
- Cleaner SIU dossiers with cited excerpts
- Better portfolio comprehension for complex treaty structures
Insurance case library
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