PATHIKA

Project Overview

We worked with a private equity fund to design this solution, addressing the challenge of managing multiple portfolio businesses, each with its own financial records and reporting needs. As the fund expanded, multiple Xero accounts led to reporting delays, payroll inconsistencies, and increased operational overhead.

Fund managers required a streamlined solution that could automatically collect and process financial data from various sources while maintaining accuracy, compliance, and scalability.

Solution: Azure Multi-Agent Architecture

The Azure Multi-Agent Architecture automates the collection, processing, and reporting of financial data across multiple businesses within the fund. By integrating with the Xero API, the solution enables streamlined financial reporting, providing fund managers with accurate and timely insights.

This architecture is highly cost-effective, leveraging Azure CosmosDB as a NoSQL database for scalable data storage and Azure Serverless Functions to ensure resources are only consumed when needed. The pay-per-use model eliminates the overhead costs associated with idle infrastructure.

Data Processing Workflow

Staff members upload financial data files (e.g., CSV format) to Azure Blob Storage, serving as an entry point for the workflow. Uploaded files trigger agent-based processing tasks via Azure Event Triggers, ensuring the correct function processes each file.

Agents generate and store output files in Azure Blob Storage, triggering further agent workloads as needed. This event-driven approach enables automated payroll aggregation, compliance checks, and financial reconciliations.

Key Agents

Payroll Agent — Aggregates and summarizes payroll data across multiple businesses. It retrieves transactions from different Xero accounts, normalizes data, and generates a unified payroll report for fund managers.

Alerts Agent — Identifies payroll-related anomalies such as salary discrepancies, duplicate transactions, and compliance issues. It automatically flags issues for review, reducing financial risks.

Custom Agent Configuration

Developers can configure additional agents to handle fund-specific tasks, such as expense tracking and compliance reporting. The system's modular design enables seamless integration of new automation processes.

Final Report Generation

After processing, agents generate output files stored in Azure Blob Storage for staff to download, ensuring an automated workflow from data ingestion to report generation.

Conclusion

By leveraging Azure Functions, Azure OpenAI Service, and the Xero API, this multi-agent architecture eliminates manual data aggregation inefficiencies. The serverless model ensures scalability, automation, and rapid deployment of new financial processing tasks, empowering fund managers with real-time financial insights.