Underwriting Automation
with AI
Extract risk indicators, financial metrics, and key exposures with confidence scores and source links.
Underwriters spend hours per submission reading broker packs, loss runs, and risk surveys.
Extract risk indicators, financial metrics, and key exposures with confidence scores and source links.
Underwriters focus on judgment calls, not data entry.
How DataStruct AI delivers Underwriting Automation
Evidence-backed AI
Outputs cite the source paragraph. A verification pass flags claims it cannot match to the cited evidence.
Insurance domain pack
Pre-configured terminology, document types, and rule packs purpose-built for insurance.
Audit trail by default
Actions are logged and claims link to source. Assemble the evidence without the fire drill.
Access control and audit
Multi-tenant architecture with RBAC and audit logs. Tenant isolation is enforced in the application layer: each tenant-scoped route resolves your workspace membership and permissions before returning anything.
More Insurance use cases
Claims Processing
Extract claim facts and coverage terms with source links, and route items to a reviewer for decision.
Reinsurance Treaty Analysis
Clause and obligation extraction across treaties, each linked to its source, for side-by-side review.
Regulatory Reporting
Metrics link back to the cited source documents, with timestamps, for human review.
Run Underwriting Automation on DataStruct AI
Tell us what you're working with. We'll spin up a tailored workspace and walk your team through it.
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