How We Automated Invoice Management & Saved 60 Hours/Yearly on Repetitive Tasks

Discover how we transformed a time-consuming, manual invoice process into a streamlined, automated system using AI, saving hours each month and minimizing errors—all with just a few hours of setup.

The Problem

For the purpose of detailed expense tracking - all non-payroll invoices have to be manually “tagged” before handing over to accounting - each file name has to contain the name of the party issuing the invoice, the date it was issued, and custom accounting code for internal expense classification. All of this was done manually by our Office Manager.

This process, which included managing around 100 invoices monthly, was inefficient and labor-intensive, creating a bottleneck in the workflow and consuming significant employee time that could be better utilized elsewhere.

What we did

We decided to automate the process using AI and EL Passion’s own AI workflow tool, BuildEL, and OpenAI’s cutting-edge GPT-4o model.

Now, the Office Manager simply uploads each invoice directly to the appropriate folders on Google Drive as they are. Once uploaded, the system automatically processes the invoice, extracting essential information from the invoice itself, checking an external database to assign the proper accounting code, analyzing the data, and generating the desired file name.

The invoices are then automatically transferred to the designated accounting folder, eliminating the need for any manual sorting or organization.

This streamlined process not only saves time but also reduces the potential for errors, allowing the Office Manager to focus on more important tasks.

How we did it

• 1 h — initial sync to discuss project requirements and provide estimates
• 4 hours — project setup and the first implementation
• 3 hours — model improvement and adjustment
• 1.5 hours — maintenance & model updating

Would it be possible without AI?

Yes, absolutely. However, achieving this level of accuracy through traditional coding, without the use of AI, would likely take several weeks instead of a couple of hours a day on the development side.

On the client side (in this case, EL Passion’s Office Manager & COO), the AI-driven approach required minimal involvement — only 1-2 hours in total. The process would have been significantly more time-consuming if the solution had been hard-coded without AI.

The outcome

The new system has cut manual workload, saving our Office Manager about 5 hours each month. The process now completes in seconds, costing less than $0.01 per invoice processed. With its scalable architecture, the model effortlessly adapts to growing volumes and future functionalities.

 

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