The frontier of AI is rapidly advancing, but among the public and even in the enterprise, an understanding of its capabilities hasn’t always kept pace. The widely held view of AI often gets stuck on the image of a sophisticated chatbot, capable of engaging in a conversation with a user and providing a response to prompts. But this way of thinking is also a limitation, boxing the technology into something as simple as trading messages and images. It misses both the nuance and full potential of state-of-the-art, real-world applications.
As businesses, societies, and technical practitioners alike seek to unlock the value of AI, tapping an expanded set of capabilities has become a top priority. Capital One has delivered a recent breakthrough by building a new multi-agentic conversational AI assistant for car buyers.
Capital One has a long history of using data, technology, and analytics to deliver superior financial services products and services for millions of customers. For over a decade, the business has been on a technology transformation journey to rebuild its tech stack, scale its technology workforce, and extend machine learning across the business. This dedication to innovation has positioned the company at the forefront of enterprises creating industry-leading AI advances today.
“We are continually exploring ways to enhance the customer experience at the frontier of AI. As we dug into new ways to improve the shopping experience with AI, we were looking at how to provide natural and satisfying interactions based on the way humans interact and reason,” says Dr. Milind Naphade, SVP of Technology, AI Foundations at Capital One. “We wanted to transform the customer experience by replacing the previous generation of conversational AI technology with an agentic approach that leverages large language models (LLMs). We knew we needed to build a solution that would be able to really interact with a customer, understand their needs, and take actions on their behalf while they searched for a new vehicle.”
The result: Chat Concierge from Capital One. The proprietary multi-agentic conversational AI assistant is custom-built to enhance the experience for car buyers and dealers alike. But answering questions and organizing information is only one part of what Chat Concierge can do.
Model advances have enabled the dawn of AI agents that are trained to work together and tackle a series of complex tasks. Each AI agent performs a specific duty based on the user’s request. Breaking a given workflow into discrete tasks and assigning each task to an AI agent can help ease the cognitive load of the user and create a more streamlined, satisfying experience. It’s almost like building a dream team where each member is assigned to a role fitting their strengths.
With Chat Concierge, multiple AI agents work together to not only provide information to the customer, but to take specific actions based on the customer’s preferences and needs. For example, one agent communicates with the customer. Another creates an action plan based on business rules and the tools it is allowed to use. A third agent evaluates the accuracy of the first two, and a fourth agent that explains and validates the action plan with the user.
In a single conversation, Chat Concierge can present information like vehicle comparisons and specifications, then take the next step by scheduling appointments and test drives with a sales team. “There is a complex workflow that is getting executed behind the scenes, but it’s all happening behind the scenes,” Naphade explains.
These advances come as a logical progression from generative AI to AI agents that understand their environment, make decisions, and take actions. This requires an underlying infrastructure where the data and application programming interfaces (APIs) are AI-ready. “We are standing on the shoulders of all the giant systems Capital One has built so far,” Naphade says. “For example, we are one of the only banks that has fully committed to a public cloud. The data-driven, machine learning heritage of Capital One precedes us.”
The possibilities for agentic AI–and future advances in the field–continue to evolve at a rapid clip. State of the art reasoning models are now designed to handle complex tasks by thinking through multiple steps and reasoning logically. Using these models to create AI agents brings the potential to help people turn insights into action for a range of sophisticated tasks that were never possible before. For instance, they have the potential to help solve real-world challenges like working together to tackle complex, PhD-level research problems; work with a company’s developers to autonomously support the entire software development lifecycle, from planning to deployment; or even help a new business create a business plan and financial models along with a logo, website, and marketing plans.
While the pace of AI innovation excels, so does the need for thoughtful approaches that balance speed with risk management. Capital One has tested, learned, and adapted its multi-agentic conversational AI workflow to create a great customer experience, in real-time, while also mitigating hallucination and errors through strong guardrails.
In continuing to advance the state of the art in AI, Capital One isn’t just inventing new tools and technology. It’s delivering the right help at the right time—with intelligent, dynamically adaptive approaches—for more than 100 million customers.
Learn more about AI at Capital One here.
