ARO System

AI-based Risk Evaluation and Operations for Construction Supply Chain Financing

Revolutionary multi-agent AI system leveraging Deepseek R1, LLaMA 3, and FinLLaMA to transform construction finance risk assessment with 98.7% accuracy and 85% time reduction.

Key Capabilities

ARO transforms construction supply chain financing through advanced AI agents working in perfect coordination

Advanced OCR

98.7% accuracy in document processing with intelligent validation

Financial Analysis

Comprehensive ratio analysis and trend detection using FinLLaMA

Market Intelligence

Real-time news collection and sentiment analysis

Risk Assessment

Multi-dimensional risk scoring with 94.3% accuracy

System Architecture

Six specialized AI agents working in perfect coordination to deliver comprehensive risk assessment

Agent 1

OCR Processing

Deepseek R1

Advanced document processing with 98.7% accuracy

Agent 2

Data Filling

FinLLaMA

Financial analysis and client card generation

Agent 3

News Collection

LLaMA 3

Market intelligence and risk tree construction

Agent 4

Report Generation

Deepseek R1

Comprehensive risk reports and sentiment analysis

Agent 5

Interactive Query

LLaMA 3

Real-time query processing and exploration

Orchestrator

Central Coordination

LLaMA 3

Workflow management and task coordination

Click on an agent to see detailed information

LLM Assignment Strategy

Agent Assigned LLM Rationale
Agent 1 (OCR Processing) Deepseek R1 Superior vision-language capabilities
Agent 2 (Data Filling) FinLLaMA Financial domain expertise
Agent 3 (News Collection) LLaMA 3 General-purpose web processing
Agent 4 (Report Generation) Deepseek R1 Comprehensive synthesis abilities
Agent 5 (Interactive Query) LLaMA 3 Conversational capabilities
Agent Orchestrator LLaMA 3 Task coordination and planning

Interactive Demo

Experience ARO's capabilities with our interactive demo using real construction company data

Company Selection

Apex Builders Limited

Hong Kong | 16+ years | Construction & Levelling

Category B

Risk Score: 0.665

Sample High-Risk Company

Hong Kong | 3 years | Small Construction

Category C

Risk Score: 0.825

Sample Low-Risk Company

Hong Kong | 25+ years | Major Contractor

Category A

Risk Score: 0.285

Select a company and click "Start Risk Assessment" to see the demo

Case Studies

Real-world validation demonstrating ARO's effectiveness in construction supply chain financing

Ting Fung Construction Limited

Hong Kong Construction Company

Processing Time

4.2 min

96.2% faster

OCR Accuracy

98.7%

Industry leading

Key Findings:

  • • 16+ years operational experience
  • • 15% market share in levelling services
  • • Strong interest coverage ratio (38.7x)
  • • Liquidity challenges identified
  • • Category B risk classification

Risk Score Breakdown:

Financial Risk
0.72
Market Risk
0.58
Operational Risk
0.45

Performance Validation

Comprehensive System Evaluation

System Performance

94.3%

Classification Accuracy

96.1%

Expert Agreement

99.2%

System Availability

3.8 min

Avg Processing Time

Efficiency Improvements

Processing Time Reduction
85%
Human Review Reduction
67%
Accuracy Improvement
23%
Cost Reduction
92.5%

Technical Documentation

Comprehensive documentation, research papers, and implementation guides

Research Paper

Complete 62-page research paper with mathematical formalization, case studies, and performance evaluation.

• Springer LNCS format

• Comprehensive evaluation

• Source code included

API Documentation

Complete REST API documentation with examples, endpoints, and integration guides.

• OpenAPI 3.0 specification

• Interactive examples

• SDK libraries

Implementation Guide

Step-by-step guide for implementing and deploying ARO in your organization.

• Deployment instructions

• Configuration examples

• Best practices

Mathematical Model

Detailed mathematical formalization of agent functions, optimization, and convergence analysis.

• Formal definitions

• Convergence proofs

• Optimization theory

Source Code

Complete source code implementation with agent classes, orchestrator, and integration examples.

• Python implementation

• Docker containers

• Unit tests included

Benchmarks

Comprehensive performance benchmarks, scalability tests, and comparison with existing solutions.

• Performance metrics

• Scalability analysis

• Comparative studies