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Invoice Processing using AI Agents

Multi-agent AI system automating invoice workflows using asynchronous pipelines and intelligent routing.

Tech Stack

PythonFastAPIMulti-Agent SystemsStreamlit

Problem Statement

Manual invoice processing is time-consuming and error-prone, requiring intelligent automation for extraction, validation, and routing.

System Architecture

Designed a multi-agent system where each agent handles specific tasks such as extraction, validation, and routing. Coordinated through asynchronous FastAPI pipelines.

Approach

Implemented planner-executor style agents to process invoices step-by-step. Focused on modular design for extensibility and fault tolerance.

Implementation Details

Developed FastAPI backend managing agent workflows, integrated document parsing logic, and built a Streamlit dashboard for monitoring system state and debugging.

Challenges & Solutions

Coordinating multiple agents, ensuring fault tolerance, and maintaining low latency in asynchronous workflows.

Results & Impact

Reduced manual processing effort and demonstrated scalable automation of document workflows.

Key Learnings

Gained insights into agent-based architectures, workflow orchestration, and real-world automation challenges.