Work — Document & Data Processing
PolicyIQ
An insurance policy comparison AI for an independent insurance agency — carrier PDFs read into a structured ontology and compared side by side.
The brief
Commercial insurance comparison runs on PDFs. Coverages, limits, exclusions, scattered across carrier documents in formats that don't match and language that doesn't reconcile. For an independent insurance agency handling submissions across multiple carriers, that reconciliation is the job—slow, repetitive, dependent on how closely each document gets read on a given afternoon.
PolicyIQ reads the documents. Carrier PDFs in; coverages, limits, and exclusions out, mapped to a structured ontology common across carriers regardless of who wrote the policy. Policies compared side by side, carrier against carrier, term against term. Every extracted claim carries an audit trail back to its source passage—no comparison asserts what the document doesn't say. Human-review checkpoints hold the line between extraction and decision. Built for operators and growing businesses; here, an independent insurance agency working commercial policy volume.
Two layers under the architecture: an LLM extraction layer, an LLM comparison layer. Cost-modeled at roughly $200 to $350 a month for a volume of 75 to 100 policies. The design is complete—twelve sections, adversarially reviewed before any production build. PolicyIQ: currently in build.
How it runs
The structure of the build, end to end — each stage hands off to the next.
Delivered
Extraction pipeline: coverages, limits, and exclusions read from carrier PDFs into a structured ontology
Cross-carrier comparison: policies aligned side by side, term against term
Audit trail: every extracted claim traceable to its source passage
Human-review checkpoints placed between extraction and decision
Twelve-section technical design, adversarially reviewed
Cost model: roughly $200–350/month at 75–100 policies/month volume
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