AI Agents

Context

Designed for insurance within the Policy onboarding stack, this agent is used before issuance (and on endorsements) to ensure the policy pack is internally consistent. Typical scenarios include reconciling the proposal/application, product T&Cs, schedule, riders, limits, deductibles, and exclusions so the final document set matches what was selected and disclosed.

What it does

The agent reads the policy documents and cross-checks terms across the pack. It reconciles limits, deductibles, waiting periods, rider names and codes, effective/expiry dates, covered items, and exclusions between the application/proposal, product wording, and the draft schedule or certificate. It flags missing riders, mismatched amounts or dates, contradictory clauses, and unreferenced attachments, and it links every finding back to the exact clause or table so reviewers can verify and correct quickly.

Core AI functions

Document classification and section parsing for proposal, T&Cs, riders, schedules, and endorsements; clause and table extraction with normalization of amounts, codes, and dates; cross-document alignment to detect discrepancies; contradiction and omission checks (e.g., rider listed on schedule but absent in wording, sum insured limit mismatch, exclusion text drift); and reason-code generation with confidence scoring to focus attention on material issues.

Problem solved

Manual reconciliation of policy terms is slow and error-prone. Mismatches between proposal, wording, and schedule lead to last-minute corrections, post-issuance endorsements, and avoidable complaints.

Business impact

Issuance is faster and cleaner: fewer issuance errors, fewer follow-on endorsements, clearer documentation for customers, and a stronger audit trail because each check is linked to source clauses.

Integration and adjacent use cases

Integration is light–moderate: the agent ingests PDFs or generated drafts from your authoring/DMS or policy admin and writes findings, links, and prompts into your onboarding or document workflow; no changes to cores are required.

Common combinations in this stack include:

• Identity & document extractor (policy) (to ensure base data is correct),

• Risk profile & disclosure analyzer (to confirm inputs behind the terms),

• Product suitability & match validator (to verify the selected options align with objectives and risk),

• Beneficiary & nominee validator (where applicable to the product), and

• Jurisdictional compliance agent (policy) (to confirm local wording and disclosure requirements are reflected).