Driving Operational Efficiency at Adyen through Large Language Models (LLMs)

Everyone's been talking about OpenAI’s ChatGPT, and it's easy to see why. It has sparked the curiosity of everyone in the world, including Adyen teams, leading to numerous requests and initiatives inside the company. Some frequently discussed initiatives revolve around interacting with a knowledge base of documents and improving our operations efficiency. Immediate attention was given to understanding the licensing options and ensuring the control and safe usage of the technology.

At Adyen, it took us a moment to comprehend how we could add value with such impressive technology. It is, in the end, quite common and understandable that our urge to fidget with the new technology prompts us, engineers, to find problems to solutions - instead of solutions to problems. This is in our nature, to learn and grasp technology. On the other hand, OpenAI, and others, have made it extremely convenient to leverage such power through APIs, which makes it possible to get results in a shocking short time at the expense of learning the details.

As engineers at Adyen, we don’t take emerging technology at face value and we prefer to peek under the hood, understand the dynamics, details, limitations and risks. At the same time we also assessed where we would add the most value in the organization using NLP (or an LLM) and we landed on improving our operational efficiency for our support teams. 

This is why, behind the buzz, we established a dedicated team of Data Scientists and ML engineers at Adyen’s Tech Hub in Madrid. This team is actively leveraging the possibilities offered by Large Language Models (LLMs) and Natural Language Processing (NLP) applications to streamline and improve operations.

Adyen is experiencing rapid growth and, as a technology company, we are looking for ways to scale efficiently. Therefore, at this moment, any initiative related to operational efficiency and automation is highly relevant.