By Dave DeFusco
On any given day in the United States, thousands of truck drivers spend hours scanning online load boards, searching for freight they can haul. The process is often slow and frustrating, requiring drivers or dispatchers to sift through messy data, call brokers and negotiate prices. For Tharun Prabhakar, a graduate of the Katz School’s M.S. in Artificial Intelligence, that inefficiency looked like an opportunity. Today, he is helping build technology that could transform how freight moves across the country.
At the Katz School, Prabhakar took courses taught by computer scientist Jiang Zhou. After graduating, he became a founding member of Kayaan AI, a startup developing voice-driven artificial intelligence tools for truck drivers. The goal of the company is simple to explain but technically complex to achieve: create an AI assistant that allows a truck driver to book a profitable load with a single voice command.
“Instead of drivers spending hours searching and negotiating, our system does the work in the background,” said Prabhakar. “You just talk to it, and it understands what you want, finds the best load and even negotiates for you.”
At Kayaan, Prabhakar works as what is known as a Forward-Deployed AI Engineer, a role that blends technical development with hands-on work with customers.
“My work doesn’t involve just sitting behind a screen and coding all day,” he said. “I talk directly with clients, understand their requirements and filter out the noise. Then I quickly build a proof of concept so they can see how the system will work before we develop the full product.”
The platform relies on several artificial intelligence systems working together. One central AI agent—nicknamed “Kay”—communicates with drivers through voice. Other AI agents handle specialized tasks behind the scenes.
“We have two or three different AI systems running behind the app,” said Prabhakar. “The main agent talks to the driver and understands their needs. When the driver finds a load they like, another agent is triggered to call the broker in real time, confirm the details and negotiate the price.”
The negotiation process can resemble a real conversation between two people. “It goes back and forth,” said Prabhakar. “It pushes the boundary as much as possible to get a better rate for the driver. At the same time, it keeps the driver informed and asks for approval before the load is booked.”
Building such a system has required solving practical challenges that don’t always appear in academic research. One of the toughest was teaching the AI to function in noisy environments.
“The biggest task was making it work in noisy conditions,” said Prabhakar. “A truck cab can have multiple voices, road noise and radio. We had to build tools so the system can recognize who the driver is and ignore background voices.”
The team also had to make sense of the messy data that dominates the freight industry. “AI alone is not enough,” he said. “Most of the data we get is very unstructured. So, we first build algorithms that extract meaning from the data and convert it into a format the AI can understand.”
The business vision behind Kayaan is supported by fellow Katz student Aquib Hussain, a student in the M.S. in Data Analytics and Visualization and contributes to the company’s strategy.
“Our vision is to build a voice-first AI co-pilot for truck drivers,” said Hussain. “Right now drivers depend heavily on dispatchers and often deal with unfair prices. What we’re building helps drivers book profitable loads themselves with a single voice command. The core team is supported across analytics, design thinking, customer insights, product feedback and go-to-market strategy as we bring this platform to life.”
The scale of the opportunity is enormous. The trucking industry in the United States alone moves more than a trillion dollars’ worth of goods each year. Even small improvements in efficiency can have huge economic impact.
Prabhakar’s journey from graduate student to startup founder reflects the growing connection between academic research and real-world technology deployment.
“It’s more than the curriculum,” he said of his time at the Katz School. “The projects and the professors guided me in understanding how real systems work. They taught me how to break complex problems into smaller pieces and build solutions step by step.”
Professor Zhou said watching students like Prabhakar translate classroom ideas into working technology is deeply rewarding.
“The initiative that Tharun and his teammates have shown is very impressive,” he said. “They are taking advanced AI concepts and applying them to a real industry problem. That kind of innovation is exactly what we hope our students will pursue.”
