Paychex trains AI model using stored data with MongoDB

THEIR CHALLENGE

Using MongoDB Atlas to support Paychex’s call center

Founded in 1971, Paychex provides complete solutions for human capital management, including payroll, human resources (HR), retirement, and benefits services, to over 745,000 clients. The company processes more than one million payrolls in a single day. Given the sensitive nature of the financial and personal information that Paychex handles, strong data security and management are essential to the company’s success.

To host its data, Paychex manages 800 instances across 140 applications, with 100 of these instances hosted on premises. In 2022, the company adopted a cloud-first strategy as part of its ongoing efforts to modernize and strengthen its infrastructure and began to explore new capabilities, such as automation and AI. In 2022, large language models (LLMs) became widely available, and Paychex saw an opportunity to boost the productivity of its HR services representatives.

Paychex operates a 24/7 call center, through which its service representatives provide in-depth answers to a range of complex customer questions, from payroll and personnel issues to benefits administration and regulatory compliance. Representatives need to be as accurate as possible because wrong answers could lead to fines for both Paychex and its clients. Furthermore, answers must comply with federal, state, and county regulations, which require representatives to navigate vast knowledge bases to find the right information. This impacts both onboarding new representatives and maintaining ongoing productivity.

By leveraging LLMs, which make diverse knowledge repositories searchable, Paychex could enable its representatives to quickly access relevant information from a unified system that integrates call and chat transcripts, internal databases, government regulations, and third-party datasets. Paychex implemented an out-of-the-box LLM and began to create a chatbot for its representatives.

As Paychex built the chatbot, it wanted to collect and analyze user interactions so that it could continually improve the solution’s performance. To do so, it added MongoDB Atlas to efficiently store and manage large amounts of interaction data.

OUR SOLUTION

Deploying MongoDB Atlas in less than one month

Paychex’s beta AI chatbot went live in April 2024. Using ChatGPT, representatives can query all of Paychex’s knowledge bases, and once ChatGPT has generated the responses, the data goes into a MongoDB Atlas store.

“We’re using our AI copilot solution, powered by MongoDB Atlas, to better support our service representatives,” said Sean Caron, Senior Manager of Data Services at Paychex. “This solution empowers them to provide an even better experience for our clients, creating a real market differentiator. It’s so much more than an internal tool.”

When users provide feedback on the quality of the model’s responses, the data stored in MongoDB Atlas iteratively retrains the out-of-the-box models. This cycle helps the models evolve and improve over time. Paychex harnesses the stored data — such as the number of people using the tool, the model’s speed, and the type of questions asked — to create visualizations and analyze trends. With these insights, the company can continually refine the AI solution so that the chatbot remains effective. The solution also remembers previous interactions, leading to more contextual and relevant responses in follow-up conversations.

Paychex deployed MongoDB Atlas in less than one month. More than 50% of Paychex’s database administrators were already trained on other MongoDB solutions, which made the transition seamless. “We took people who had never worked in MongoDB Atlas before, and they were up and running in a matter of days,” said Dave Hart, Data Platforms Manager at Paychex. “Their MongoDB skills were all transferable, so it was simple for everyone to get up to speed.”

Because MongoDB Atlas is a multicloud platform, Paychex can host applications that span multiple vendors and data tiers. MongoDB’s end-to-end automation capabilities mean Paychex can now deploy a full dataset in as little as 27 minutes across all its data centers. “Our automation-first mentality is what’s driving us to evolve,” said Caron. “MongoDB has been a great support in that space.”

OUTCOME

Enhancing accuracy and productivity with AI

Since implementing MongoDB Atlas, Paychex’s HR service representatives obtain solutions faster and more efficiently than before, which leads to major productivity gains. Plus, with the array of knowledge bases at each representative’s fingertips, the solution drives better, more consistent experiences for Paychex’s clients. “Anything you can do to help make individual workers more productive is a win,” said Hart. “We see our AI solution as a way to make good service representatives great.”

As Paychex moves forward, the company will continue refining the AI solution’s accuracy and effectiveness. To do so, Paychex will invest in model training and data curation. “As with anything that’s data driven, the quality of the data and how it’s curated to solve the problems at hand will define the results,” said Hart. “We’ve found MongoDB to perform at the level that we need.”

Paychex will also continue its migration to the cloud. The company expects that MongoDB will be at the forefront of its cloud journey and AI strategy. “This was our first big MongoDB Atlas project, and it went incredibly well,” said Hart. “MongoDB proved to be an excellent platform for us, and we already have other projects planned that use it.”

To learn more, visit MongoDB Atlas.