Facilitate Claims Data Aggregation from Disparate Systems

Claims data often resides in multiple legacy systems and diverse formats (databases, documents, spreadsheets), making it difficult for adjusters to get a unified view. LLMs, particularly within a Retrieval-Augmented Generation (RAG) framework, can help query and aggregate relevant information from these disparate sources based on natural language prompts from the adjuster. This provides a more comprehensive context for decision-making without complex manual data gathering.