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Connect your insurance knowledge, policy systems and claims platform through one conversational experience.
Policyholders should not need a support agent every time they want to understand a benefit, check a claim or complete a routine insurance request. The Insurance AI Assistant creates a conversational layer across your existing insurance knowledge and core systems, helping users move from question to answer, and from answer to action, through the same experience.
Use approved insurance and product content to respond to questions about benefits, coverage, premiums and other product information.
Connect to existing policy and claims systems to provide policy details, claim status and claim history after the relevant ownership checks.
Guide users step by step through processes such as claim submission, collecting required information and documents before passing the request to the core claims system.
Help users retrieve relevant policy, plan, member and beneficiary information after validating the policy relationship.
Answer questions about coverage, benefits, premiums, sum assured and other product information using indexed insurance content and product data.
Let users ask for a claim update conversationally and retrieve the corresponding status and progress information.
Allow users to review claims associated with their policy and navigate through claim history without repeating information already provided.
Guide policyholders through policy validation, claim type, amount, treatment date and required document collection before submitting the claim.
Keep structured workflow state between messages so users can continue a multi-step request from where they left off instead of restarting.
For a claim submission, the same orchestration layer can continue the conversation across multiple steps until the required information and documents have been collected.
Policy and member ownership can be checked before sensitive lookups or claim actions proceed.
Policy and claim retrieval can combine semantic relevance with identifier-based filtering, avoiding inappropriate near-match results.
Multi-step processes such as claim submission use explicit workflow state rather than depending solely on an LLM to remember what happens next.
The retrieval architecture supports in-process query embeddings, reducing the need to send query text to an external embedding service.
The application uses a common LLM interface, allowing the underlying model integration to be configured independently of the orchestration logic.
The assistant sits above existing insurance systems as a conversational and orchestration layer instead of replacing policy or claims platforms.
The solution follows a modular architecture designed to connect with existing insurance environments, sitting above your policy administration and claims platforms as a conversational and orchestration layer.
