Case Study: Automated processing of invoices delivered to an email inbox

Process automation is becoming a key element of operational efficiency in enterprises. Regardless of the industry in which a company operates, as it grows, the volume of processed documents increases at a rapid pace. Therefore, the need to implement modern solutions in the form of automation becomes inevitable. In this article, we present a case study of building an AI agent for the automatic processing of invoices delivered to an email inbox—an implementation we carried out for one of our clients.

Introduction to the problem

As our client's company grew, the number of documents that needed to be processed increased. A manual approach to invoice management, based on entering and archiving documents by hand, turned out to be inefficient. The process was time consuming, prone to errors, and lacked standardization. When the person responsible for processing invoices was absent, others had to learn and take over the entire process during their absence. In response to these challenges, we decided to implement an automation system that would minimize these problems.

Implementation goals

The main goals behind the implementation included:

• automating the retrieval of invoices from email messages based on predefined rules, to eliminate the need for constant inbox monitoring,
• saving documents to a Google Drive platform in the appropriate folder, to store files in a centralized and standardized location,
• automatically registering invoices in the CRM system with complete information and a link to the Google Drive file,
• reducing manual work and errors associated with data entry, and securing the entire process in case the employee responsible for it is absent.

Achieving these goals made it possible to reduce the time required for process handling and introduce a level of standardization. The client's primary objective was to ensure that the employee, instead of wasting time on routine tasks, could focus on more strategic responsibilities.

Technologies used in the project

To accomplish the intended objectives, we utilized the following technologies:

• n8n - serves as the orchestration engine for workflows, allowing for the definition and automatic triggering of each process step. Thanks to n8n, it was possible to coordinate task execution without manual operations and build a complete AI agent.
• Google Drive API - Google Drive is responsible for securely storing and managing files in the cloud, and the API allowed for remote integration with the service.
• Gmail API - used to retrieve emails from a specified company mailbox operating via Gmail. With the API, we could extract both the email content and invoice attachments.
• OCR and AI - we used text recognition technologies such as Tesseract to extract data from invoices. The OCR technology is additionally supported by AI models (OpenAI), which process the extracted data for the next workflow stages.
• CRM API - the client's custom CRM system stores data about contractors and payments. Thanks to the API, we were able to properly send the data into the CRM.

Solution architecture

The designed automation architecture consisted of several key steps:

1. Periodic listening and reading of incoming email messages.
2. Downloading the attachment and saving it to Google Drive.
3. Using OCR to extract data from the invoice, which was then processed by appropriate AI models to prepare the final data set.
4. Sending the data to the CRM system.

Thanks to building the architecture around the use of webhooks, schedules, and filters in n8n, the process became not only faster, but its implementation time was also significantly reduced. By using n8n, we avoided the need to develop dedicated software and instead created a single workflow that runs as an AI agent.

Implementation process

The project implementation followed several stages:

1. Analysis of invoice sources: we examined various formats and sender addresses to prepare a set of criteria and filters that the AI agent should follow when monitoring the mailbox and identifying relevant emails.
2. Designing and testing the workflow: we created and tested appropriate processes in n8n along with integrations with external services and cyclic triggering, to continuously monitor the mailbox.
3. Integration with Google Drive: we integrated the automatic saving of documents into a designated folder on Google Drive
4. Training AI models: we focused on successfully implementing OCR, which reads data from the invoice, and then the extracted data, along with general information about the contractor, is sent to the AI model, which appropriately merges and prepares the data for the CRM system.
5. Integration with CRM: we integrated with the CRM system API, allowing the previously prepared data to be correctly transferred to the target CRM system.
6. Testing and production launch: we conducted detailed tests before full deployment, which included verifying the operation of individual steps of the AI agent as well as the effectiveness of data extraction using OCR.

Effects of automation

The implementation of the system delivered a number of tangible benefits:

• Each month, a significant number of work hours were saved that had previously been required for daily invoice handling. The saved time allowed for more efficient use of resources;
• Automation reduced the risk of errors in invoice registration, which contributed to improved data quality. The number of mistakes that previously occurred during manual data entry into the CRM system dropped significantly. A new standardization of the entire invoice processing workflow was also established;
• Employees can now focus on more valuable tasks and are no longer burdened with routine work. This increased their job satisfaction.

Conclusions and plans for further development

The implementation of the system was fast and did not require a large budget, while delivering a number of measurable benefits. The project also opened up new development opportunities. In the future, the system could include:

• expanding the system with additional data sources such as B2B or SaaS platforms;
• using artificial intelligence to generate cost summaries and expense recommendations;
• using artificial intelligence to automatically respond to specific emails (e.g., acknowledging receipt of an invoice, requesting additional information);
• parameterizing the AI Agent to handle similar document workflow cases in other departments (e.g., HR);
• sending Slack channel notifications when a new invoice is added to the CRM system.

The case study we presented on automatic processing of invoices delivered to an email inbox demonstrates how modern technologies can revolutionize business processes. By implementing innovative solutions, the company gained not only time savings but also increased operational efficiency.

We encourage other companies to consider similar solutions that can bring tangible benefits to their operations. The solution we showcased is one of the first steps that can be introduced in any company, and at the same time, its implementation is relatively quick and low cost.

If you're thinking about implementing AI in your company, deploying a similar solution can be the first and fastest step in the long journey of automation adoption in your business.