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Empowers HR teams to deliver fast, accurate, and personalized employee support through conversational AI, automated knowledge management, and seamless HR system integration.
Claim Digital Agent
Automates data extraction from medical documents and builds a personalized knowledge base, enabling faster claims processing and smarter health insurance operations.
#Insurance #HealthClaims #AI #Automation #DocumentUnderstanding #GenerativeAI #KnowledgeBase
Business Challenge
Processing health insurance claims requires reviewing diverse documents - such as invoices, certificates, and medical reports - that often vary in format and quality, making the process time-intensive, error-prone, and increasingly unsustainable as claim volumes grow. Insurance companies struggle with disparate data formats, inconsistent information extraction, and maintaining accuracy while meeting customer expectations for faster settlements. Beyond processing speed, there’s the need to transform unstructured documents into structured, reusable knowledge to support decision-making, fraud detection, and ongoing service improvement.
Solution Overview
Our Claim Digital Agent transforms the claims liquidation process through an intelligent document processing system powered by advanced OCR and AI agents. It automatically extracts key metadata - including policy details, beneficiary information, and medical services - from unstructured documents, classifies claims by type and complexity, and normalizes the data into a standardized, system-ready format.
Beyond extraction, the solution builds a personalized knowledge base for each customer, continuously refining their profile and history. This structured repository becomes progressively more intelligent with each processed claim, enabling efficient visualization, navigation, and reuse of customer data across the organization. A conversational interface provides natural language access to the knowledge base, allowing users to retrieve information related to claims, settlements, and customer history quickly and accurately.
The solution integrates seamlessly with existing workflows, fraud detection systems, and monitoring tools, supporting real-time claim status tracking, automated validation, and advanced analytics for process optimization and anomaly detection. By reducing manual intervention and unlocking the value of claim-related data, the application accelerates settlement, improves operational efficiency, and supports smarter, more transparent insurance operations.
Technical Implementation
This Generative AI solution was built with:
Document Acquisition and Preprocessing
Ingests PDFs, images, or scanned forms through a containerized pipeline that can be deployed on-premises or in the cloud. Preprocessing steps include de-skewing, de-noising, and quality checks to ensure optimal OCR accuracy.Enhanced OCR Layer
Converts PDFs and other scanned documents into image files where needed, then applies OCR to produce machine-readable text. Quality improvements such as de-noising or PDF-to-image conversion ensure more accurate extraction in subsequent steps.AI-Driven Entity Extraction
Uses large language models and domain-specific AI to recognize and extract contextually relevant information from unstructured text, even when documents follow non-standard formats.Classification and Categorization
Classifies procedures or medical services into standard categories, allowing alignment with existing business rules, policy engine requirements, or regulatory frameworks.Knowledge Graph Construction
Organizes extracted information into a semantic network that connects claims, treatments, diagnoses, and coverage details, enabling contextual understanding of each policyholder's health insurance journey.Validation Layer
Implements a configurable rule engine—potentially leveraging business logic or domain ontologies—to cross-verify consistency among extracted fields. This layer can incorporate reference data sources to detect mismatches or omissions, routing anomalies to a human review queue.
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