AI Agent Multi-Agent DME Billing Reconciliation System

Intelligent Matching Agent

Performs multi-field composite matching using semantic similarity (vector embeddings) and fuzzy matching algorithms (Jaro-Winkler, Levenshtein). Applies weighted matching across HCPCS code, patient name semantic similarity, equipment description fuzzy match, and date proximity. Achieves high match rates with configurable confidence thresholds, flags discrepancies by severity.

View Core Logic Back to Worker

Part of Multi-Agent DME Billing Reconciliation System

Portal: Nexgile Healthneuron Nexus

Agent ID: matching-engine

Problem Statement

The challenge addressed

Delivery records and billing entries often don't match exactly due to typos, timing differences, and data entry errors—manual matching is time-consuming and misses discrepancies.

Core Logic

How the agent solves it

Performs multi-field composite matching using semantic similarity (vector embeddings) and fuzzy matching algorithms (Jaro-Winkler, Levenshtein). Applies weighted matching across HCPCS code, patient na... Performs multi-field composite matching using semantic similarity (vector embeddings) and fuzzy matching algorithms (Jaro-Winkler, Levenshtein). Applies weighted matching across HCPCS code, patient name semantic similarity, equipment description fuzzy match, and date proximity. Achieves high match rates with configurable confidence thresholds, flags discrepancies by severity.

System Navigation

Explore related components

Portal

Nexgile Healthneuron Nexus

Digital Worker

Multi-Agent DME Billing Reconciliation System

Current Agent

Intelligent Matching Agent

Here