Adaptive Content Flow Interface for Guided Digital Claim Intake

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Solution Overview

Problem

Existing Software as a Service (SaaS) providers face inefficiencies in claim processing, particularly in insurance claims, due to time-consuming manual procedures and suboptimal communication with users and policy providers, leading to frustration and delays.

Innovation Solution

A computing system that utilizes artificial intelligence and machine learning to optimize claim processes by generating AI prompts, performing guided content capture, and implementing dynamic scripting and engagement monitoring to streamline information gathering, automate negotiations, and provide intelligent service recommendations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual procedures are used for claim processing, then communication between users and policy providers can be personalized, but processing time increases and efficiency decreases

Engineering Contradiction:

Improvecommunication qualityVSAvoidclaim processing time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system implements self-service capabilities where users can initiate and track claims independently through automated interfaces. The chatbot and portal enable users to submit claims, upload documents, and receive updates without constant manual intervention from adjusters, reducing processing time while maintaining service quality.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processes are replaced with automated systems including AI chatbots for initial claim intake, machine learning models for fraud detection, and automated document verification systems. This substitution eliminates manual paperwork and accelerates claim processing while preserving personalized communication through automated messaging.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated systems are implemented to reduce processing time, then efficiency improves, but communication personalization and user engagement may deteriorate

Engineering Contradiction:

Improveclaim processing efficiencyVSAvoiduser engagement quality

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

An AI chatbot serves as an intermediary between users and human adjusters, handling routine inquiries and claim submissions automatically. This intermediary maintains continuous engagement with users through personalized messaging while routing complex cases to human agents, preserving engagement quality without sacrificing processing efficiency.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system dynamically adapts its communication style and level of automation based on user needs and claim complexity. Simple claims receive fully automated processing with personalized notifications, while complex cases are escalated to human agents, creating a dynamic balance between efficiency and engagement quality.

Inventive Principle:

Principle #15Dynamics

3Measurement precision

If comprehensive information gathering is performed manually, then accuracy of claim assessment improves, but time consumption and resource usage increase

Engineering Contradiction:

Improveclaim assessment accuracyVSAvoidinformation gathering time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary information gathering automatically through chatbot interviews and document uploads before human adjuster review. Users complete detailed questionnaires and upload supporting documents in advance, so when human agents review the claim, the foundation work is already done, improving accuracy without increasing their time burden.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback loops where machine learning models continuously learn from claim outcomes and adjust their information gathering strategies. The chatbot adapts its questioning based on user responses and claim patterns, ensuring comprehensive data collection while optimizing the information gathering process over time.

Inventive Principle:

Principle #23Feedback

4Reliability

If multiple manual review steps are implemented for fraud detection, then detection accuracy improves, but processing complexity and time increase

Engineering Contradiction:

Improvefraud detection accuracyVSAvoidprocessing system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

Manual fraud review processes are replaced with automated machine learning models that analyze claim data, document authenticity, and user behavior patterns. These models perform preliminary fraud screening automatically, flagging only suspicious cases for human review, thereby maintaining high detection accuracy while reducing overall system complexity and processing time.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20260050930A1Facilitating digital requests through an adaptive content flow interface

Publication Date: 2026.02.19 ASSURED INSURANCE TECH INC

AI summary

A computing system can dynamically generate a user interface comprising a content flow for a call representative to advance a claim process with a user, the user interface including a digital request feature that enables the call representative to make digital requests to the user. In response to the call representative making a first digital request to the user using the digital request feature, the computing system can initiate communications with a computing device of the user to facilitate the first digital request.