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Extract Invoice Data Automatically Using LangChain

In this article, I’m sharing an app I built to automate invoice processing using image recognition and language models. The goal is simple: take scanned or photographed invoices (in JPG, PNG, or PDF format) and extract structured data in JSON.

Under the hood, the system uses OpenAI’s GPT-4o (GPT-4 Vision) model via LangChain, and it’s wrapped in a lightweight FastAPI backend built with Python. The app can batch process files, run locally or in a container, and outputs clean JSON ready for downstream systems like accounting tools or CRMs.

Tech Stack & Architecture

The app is structured with a modern, API-first architecture:

Backend: Python with FastAPI, using LangChain + GPT-4o for invoice processing

Authentication: AWS Cognito for secure, scalable user auth

Database: MongoDB for storing processed invoice data and metadata

Frontend: A Next.js app handles the UI and connects to the backend via API

The authentication layer with AWS Cognito makes it easy to manage user sign-ups, login access. Invoice data and any synced product info are stored in MongoDB, which works well with JSON-like structures.
On the frontend, Next.js provides a fast and reactive UI that lets users upload invoice images, view extracted data, and manage syncing.

Sync Invoice Items with Product Barcodes

Once the app extracts line items from the invoice such as product names, you can take it a step further by syncing these items with your internal product database. This allows you to:

  • Match items by name
  • Automatically assign or update barcodes
  • Link products to existing inventory systems
  • Detect mismatches or missing items

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