Enterprise Multi-Agent Reconciliation System
Deploys a fleet of **6 specialized AI agents** that execute a **9-phase workflow** with multi-pass matching algorithms (exact O(n), fuzzy, ML similarity), 5 parallel anomaly detection methods (Z-Score, IQR, Isolation Forest, Benford's Law, Velocity), and auto-resolution of breaks..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Data Command Center - Multi-agent orchestration dashboard displaying Books of Record management, reconciliation periods, target funds, and agent configuration with real-time reconciliation status and algorithm thresholds
Live Operations Center - Real-time monitoring of all 6 AI agents (ARIA, NEXUS, VECTOR, SENTINEL, RESOLVER, GUARDIAN) showing agent trigger status, workflow phases, data load times, and active event tracking with live event feed
Mission Complete - Comprehensive reconciliation summary dashboard showing transaction counts, match rates, anomalies detected, execution summary with key findings, data inconsistencies, significant breaks, multi-pass matching, and process summary with agent insights
Deploying AI Agent Team - Agent deployment status interface displaying deployment progress for all 6 specialized agents (ARIA, NEXUS, VECTOR, SENTINEL, RESOLVER, GUARDIAN) with status indicators, online status, anomaly detection, and communication checks
AI Agents
Specialized autonomous agents working in coordination
ARIA - Orchestrator Agent
Complex reconciliation workflows require coordinated execution across multiple specialized tasks with real-time monitoring, exception handling, and load balancing across agent resources.
Core Logic
Serves as the central **workflow coordinator** using GPT-4 Turbo (temperature: 0.3, 4,096 tokens). Manages the 9-phase execution pipeline, handles task prioritization and assignment, coordinates inter-agent communication, monitors performance metrics, and escalates exceptions. Implements the ReAct pattern (Observe → Reason → Plan → Act) for decision-making.
NEXUS - Data Engineer Agent
Fund data exists across multiple disparate sources with inconsistent schemas, missing fields, and varying data quality that must be normalized before reconciliation can proceed.
Core Logic
Powered by Claude 3 Opus (temperature: 0.1, 8,192 tokens) for high-accuracy data processing. Extracts data from all 5 Books of Record, performs schema validation and normalization, assesses data quality scores, detects missing data patterns, and standardizes formats across sources. Handles 8,234+ transactions per extraction cycle.
VECTOR - Matching Analyst Agent
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
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.
SENTINEL - Risk Detective Agent
Hidden anomalies, potential fraud, and unusual transaction patterns across large datasets require sophisticated statistical and ML-based detection that manual review cannot achieve at scale.
Core Logic
Runs **5 parallel anomaly detection algorithms** using Claude 3 Opus (temperature: 0.4). **Z-Score Analysis**: Detects values beyond 3σ. **IQR Method**: Quartile-based outliers. **Isolation Forest**: 10-tree ensemble with O(n log n) complexity. **Benford's Law**: First-digit frequency analysis for manipulation detection. **Velocity Checks**: Burst detection in 60-min sliding windows. Achieves **98.7% detection accuracy**.
RESOLVER - Resolution Expert Agent
Reconciliation breaks (timing differences, FX rounding, mapping mismatches) require categorization and resolution proposals that historically required senior accountant expertise.
Core Logic
Powered by GPT-4 Turbo (temperature: 0.2, 2,048 tokens) for precise financial reasoning. Categorizes breaks by type (TIMING, ROUNDING, MAPPING, UNRECONCILED), applies auto-resolution rules for known patterns, generates journal entry proposals, adjusts settlement timing, and calculates resolution confidence scores. Achieves **85%+ auto-resolution rate**.
GUARDIAN - Compliance Auditor Agent
Regulatory compliance requires complete audit trails, four-eyes principle enforcement, and documentation for SOX, SEC Rule 17a-4, and SOC 2 requirements that are difficult to maintain manually.
Core Logic
Uses Claude 3 Opus (temperature: 0.1, 4,096 tokens) for high-accuracy compliance validation. Validates all actions against SOX requirements, generates immutable audit trails with timestamps and actor tracking, enforces segregation of duties, produces regulatory reports, and maintains complete data lineage from source to resolution.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization