When LMI was tasked by a large healthcare client to come up with a simple way to help users select insurance plans, we didn’t spend hours reinventing the wheel to come up with an extravagant tool. Instead, our team members put their heads together to use easily integrated, practical tools our client could quickly implement and adapt.
Greg Pekar, a consultant in the Advanced Analytics service line at LMI, worked with his team, including data science intern Chris Geier, to develop a prototype chatbot that enabled the client’s customers to easily access information and FAQs. The tool integrates artificial intelligence (AI) from a major cloud platform to provide interactive recommendations that improve the user experience.
“The inspiration for this prototype sparked with an internal tool we already used at LMI to help us choose healthcare plans or find answers to simple questions like ‘What is a deductible?’ or ‘How much will my copay be?’” said Pekar. “The data existed on a platform somewhere; it was about using the right tools to organize and pull it.”
Pekar came to LMI as an intern in 2013 and now works as a data science consultant. His role has shifted since leaving LMI to finish school, attending graduate school at Cornell Tech, and returning to the company. Most of his work involves improving LMI’s products, such as the out-of-pocket-cost calculator created for the Center for Consumer Information and Insurance Oversight, and brainstorming efficiencies to put into place.
Geier, a third-year computer science student at the University of Virginia (UVA) and current LMI intern, has always been interested in machine learning and analytics. He founded the Machine Learning Club at UVA, an organization designated to collect resources and information about machine learning and share it with interested parties. It also enables students in the AI field to stay connected and bounce ideas off each another.
“I’m interested in the processes of how machines learn from users, data, or other machines, and it’s been incredible to put my ideas into action at LMI,” said Geier. “After a chance encounter with LMI’s data science director at a career fair, I knew this was the right place for me to use my talents and explore my interests.”
The two LMIers work with their team to test the prototype functions that their healthcare client will eventually implement. Once successfully integrated into the system, it will pave the way for deploying new analytics operating environments for the Department of Defense and other agencies. They’ve also started brainstorming other uses for the tool, including a streamlined way to ask inter-organizational questions, such as who is a contact for a certain department or how to best obtain funding for a white paper. The tool will afford easy access to LMI’s knowledge base and make things quicker, cost-effective, and more efficient—our ultimate goal for everything we do.