🧾 AMACS - Automated Multi-Agent Audit System

AMACS is an intelligent, multi-agent ecosystem built on CrewAI that automates the end-to-end financial auditing process. By orchestrating a team of specialized AI agents, AMACS transforms raw financial data into comprehensive, risk-assessed audit reports with human-level reasoning.

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🧠 System Architecture

AMACS utilizes a sequential and hierarchical task execution model where agents hand off verified data to one another.

graph TD
    User((User)) -->|Uploads Data| UI[Streamlit Interface]
    UI -->|Triggers Crew| Orchestrator{CrewAI Orchestrator}
    
    subgraph Agents
    Orchestrator --> A1[Data Ingestor]
    A1 -->|Clean Data| A2[Compliance Agent]
    A2 -->|Policy Gaps| A3[Fraud Analyst]
    A3 -->|Risk Flags| A4[Lead Auditor]
    end
    
    A4 -->|Synthesis| Report[Final Audit Report]
    Report -->|Display| UI

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🚀 Overview

AMACS is a multi-agent AI system built using CrewAI that automates financial auditing workflows including:

• Data ingestion (ETL)
• Compliance validation
• Fraud detection
• Risk-based audit reporting

🧠 Architecture

User → Streamlit UI → CrewAI Agents → Data Ingestor → Compliance Agent → Fraud Analyst → Lead Auditor → Final Audit Report

⚙️ Tech Stack

• Python
• CrewAI (multi-agent orchestration)
• OpenRouter (LLM backend)
• Streamlit (UI)
• Pandas + DuckDB (ETL)
• ChromaDB (memory - upcoming)

📊 Features

• Multi-agent collaboration
• Explainable fraud detection
• Compliance rule engine
• Automated audit report generation
• Risk scoring system

▶️ Run Locally

git clone https://github.com/19Vermouth/amacs-audit-system.git
cd amacs-audit-system

python -m venv .venv
.venv\Scripts\activate

pip install -r requirements.txt
streamlit run app.py

🔐 Environment Setup

Create .env file:

OPENROUTER_API_KEY=your_key_here

📸 Sample Output

• Compliance violations
• Fraud alerts with risk score
• Final audit report

🚀 Future Scope

• RAG for compliance documents
• Agent memory system
• Advanced fraud ML models
• Dashboard visualizations

👨‍💻 Author

Ishaan Kar