TL;DR: I built a multi-agent system that audits invoices, detects fiscal inconsistencies, and generates compliance reports — integrated with Odoo ERP and standalone databases.

The Problem

Tax auditing for small and medium businesses in Tunisia is manual, error-prone, and slow. Most accounting firms rely on Excel and manual checks. Regulations change frequently, and keeping up is a full-time job.

I wanted to build something that could ingest financial data, run audit rules automatically, and produce compliance reports — without needing a team of accountants.

The Architecture

The system uses a LangGraph-based multi-agent architecture:

Agent 1: Data Ingestion Agent

• Connects to Odoo ERP or standalone SQL databases
• Extracts invoices, ledgers, and financial statements
• Normalizes data into a unified schema

Agent 2: Audit Agent

• Applies tax rules against the data
• Detects anomalies: missing invoices, misclassified expenses, VAT discrepancies
• Flags items for human review

Agent 3: Reporting Agent

• Generates compliance reports
• Produces a summary of findings with risk levels
• Suggests corrective actions

Orchestrator

• LangGraph manages the flow between agents
• Handles state, retries, and error recovery

Technical Challenges

Schema Mismatch: Every Odoo instance is customized differently. The ingestion agent had to handle dynamic schemas — detecting table structures at runtime and mapping them to a canonical audit model.

Multi-Agent Coordination: Getting three agents to work together without stepping on each other's state was the hardest part. LangGraph's checkpointing was essential here.

Regional Tax Rules: Tunisian tax law isn't well-documented in English. Building the rules engine meant working directly with Arabic and French regulatory texts.

What's Next

• Real-time invoice validation
• Multi-company support
• A dashboard for non-technical accountants

The repo is at github.com/HENI-MOHAMED/Audit-Agent.

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Built with Python, FastAPI, LangGraph, Odoo, and a lot of coffee.