AI Agent Enterprise Multi-Agent Reconciliation System

VECTOR - Matching Analyst Agent

Executes **3-pass hierarchical matching** using GPT-4 Turbo (temperature: 0.2). **Pass 1**: Exact matching with O(n) hash map lookup (99-100% confidence). **Pass 2**: Fuzzy matching using Levenshtein distance with configurable tolerances (85%+ threshold). **Pass 3**: ML similarity using cosine similarity on feature vectors. Achieves 96.5% overall match rate.

View Core Logic Back to Worker

Part of Enterprise Multi-Agent Reconciliation System

Portal: Nexgile CapFlow Vault

Agent ID: vector

Problem Statement

The challenge addressed

Transaction matching across multiple books requires handling exact matches, near-matches with timing differences, and complex ML-based similarity detection while maintaining high confidence scores.

Core Logic

How the agent solves it

Executes **3-pass hierarchical matching** using GPT-4 Turbo (temperature: 0.2). **Pass 1**: Exact matching with O(n) hash map lookup (99-100% confidence). **Pass 2**: Fuzzy matching using Levenshtein... Executes **3-pass hierarchical matching** using GPT-4 Turbo (temperature: 0.2). **Pass 1**: Exact matching with O(n) hash map lookup (99-100% confidence). **Pass 2**: Fuzzy matching using Levenshtein distance with configurable tolerances (85%+ threshold). **Pass 3**: ML similarity using cosine similarity on feature vectors. Achieves 96.5% overall match rate.

System Navigation

Explore related components

Portal

Nexgile CapFlow Vault

Digital Worker

Enterprise Multi-Agent Reconciliation System

Current Agent

VECTOR - Matching Analyst Agent

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