Sunder offers an AI‑powered document agent that extracts and organizes information from insurance claim packets, automatically linking each data point to its source page. The system highlights low‑confidence fields for human review and delivers claim reports with verifiable evidence, streamlining the claims processing workflow for insurers and adjusters.
Funding
Funding not disclosed
Founders
Product
Problem
Underwriters must manually review large, heterogeneous claim packets to locate and verify key information such as medical expenses, often spending extensive time cross-referencing documents and dealing with low confidence in extracted data.
Solution
Sunder offers an AI‑driven document agent that ingests entire claim packets, automatically identifies relevant documents, and extracts claim‑related fields with precise page citations. The system highlights any low‑confidence extractions for human review, ensuring accuracy while reducing manual effort. Extracted data is compiled into a complete claim report that includes source references, enabling underwriters to validate information quickly and confidently. By combining natural‑language understanding with citation tracking, Sunder streamlines the underwriting workflow and minimizes verification bottlenecks.
Target Audience
Primary users are insurance underwriters and claims processing teams that handle complex, multi‑document claim submissions.
Features
- Automatic classification of documents within a claim packet and identification of supporting evidence
- Extraction of key claim fields (e.g., medical expenses) with exact page-number citations
- Confidence scoring for each extracted field with low‑confidence items routed to a review queue
- Generation of a consolidated claim report that links all data points to their source documents
- AI model trained on insurance claim language to understand context and relationships across documents