A 3-Step Process for Processing Invoices and Contracts with AI

Your accountant might be spending up to 30% of their daily work time just re-typing data from PDF invoices and contracts into software. This is a massive waste of resources and the primary cause of data entry errors.

The Manual Paperwork Problem

As a business grows, the volume of documents to be processed increases. Every day, dozens of emails with attachments arrive. Downloading them, reading line by line, searching for tax IDs, and entering them into Excel is not only tedious but also highly prone to mistakes. A single mistyped zero can lead to significant tax or payment issues.

Traditional Optical Character Recognition (OCR) technology has been around for a long time, but it has a fatal flaw: it requires fixed templates. Invoices from hundreds of different suppliers with varying layouts will paralyze an old OCR system. Modern Generative AI completely changes this by offering the ability to read and understand context much like a human does.

Step 1: Collection and Text Recognition

Everything begins when an email containing an invoice or contract arrives in the company’s inbox. Instead of manual downloads, an automation workflow automatically captures these attachments as soon as the email hits the server.

The file is then pushed through multimodal AI models like Gemini 1.5 Pro or GPT-4o. At this stage, the AI acts as a set of “electronic eyes.” It doesn’t just extract text; it understands the structure of the document, distinguishing between tables, signatures, and stamps.

Step 2: Intelligent Classification and Information Extraction

This is where AI demonstrates its core power. The system is provided with a detailed prompt so it knows exactly which data fields to look for.

For invoices, the AI automatically finds the vendor name, tax ID, total amount, VAT, and date. For contracts, it can identify payment terms or validity periods. If a business has complex internal regulations, Building Internal AI with RAG: Using Enterprise Data will help the system automatically cross-reference information on new contracts with current company policies to flag potential risks.

Step 3: Verification and Pushing Data into the System

Extracted data should not be pushed directly into the accounting system immediately. A standard process always requires an automated verification step. The system cross-checks tax IDs against national databases or recalculates the total amount to see if it matches the itemized details.

Once everything is validated, the automation platform creates a new record in the ERP software or adds a standardized data row to Google Sheets. At this point, the accountant only needs to open the system, perform a quick final check, and hit the “Approve” button.

Implementation Guide for Small Businesses

You don’t need to hire a team of developers to build software from scratch. Current no-code tools are powerful enough to assemble this workflow.

1. Set up an automated email intake flow using Make or Zapier. Filter for emails containing keywords like “invoice” or “contract.”
2. Connect the Google Gemini API to read the PDF file. Request the AI to return data in a structured JSON format.
3. Push this JSON data into Google Sheets or accounting software via API.
4. Send a notification via Slack or Zalo to the accountant whenever a new invoice has been processed.

This “API stitching” approach is quite similar to Automating Customer Service: Reduce Response Time by 70%. The core of the solution lies in designing the data flow.

Frequently Asked Questions

Will invoice data be leaked when using AI?

If you use free versions designed for end-users (like the web version of ChatGPT), your data might be used to train models. However, when using paid APIs from providers like Google Cloud or OpenAI, the privacy terms clearly state that your data is not used for training and will be deleted after a short period.

Does AI ever misread amounts?

It is possible. AI occasionally experiences “hallucinations.” That is why Step 3 above is so important. Asking the AI to recalculate the total based on individual line items is the best way to force it to cross-check its own results.

How much does it cost to run this system?

Current AI API costs are very low. With speed-optimized models like Gemini 1.5 Flash, reading and extracting a single page of an invoice typically costs less than 100 VNĐ. The main cost lies in maintaining accounts for automation platforms like Make or n8n.

Real-world Perspective on Document Automation

Many people fear that AI will take away administrative jobs. Reality shows the opposite. AI only takes away the most boring and low-value tasks—copying data from one place to another. By freeing up 30% of their daily time from typing invoices, your staff will have the bandwidth for more important tasks like cost analysis, negotiating with suppliers, and optimizing cash flow for the business.