Background

Sharp Transportation, founded in 1970 by John T. Sharp in Wellsville, Utah, has grown from a small family-owned operation into a leading nationwide logistics company. Located in Cache Valley, just 75 miles north of Salt Lake City, Sharp Transportation remains rooted in its small-town values while expanding to include 200 trucks, 500 trailers, 25 outside carriers, and a dedicated team of 170 employees. Sharp has steadily grown its operations to include warehouses and offices in Salt Lake City, Twin Falls, Seattle, and beyond.

Focused on their commitment to operational excellence, driver success, and customer satisfaction, Sharp partnered with Boon to implement cutting-edge AI agents to optimize their backhaul load sourcing processes, and maintain the company’s reputation for dependable, efficient logistics services.

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Testimonial

"We're now at the front of the line instead of the back of the line for backhauls. We're finding loads that we normally wouldn't."

— Kevin Boydstun, Operations, Sharp Transportation

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Challenges

Sharp and Boon identified key challenges in their backhaul and load sourcing processes, which impacted operational efficiency and profitability:

• Manual backhaul sourcing process: Sharp’s logistics team manually searched for backhaul loads, often spending hours navigating load boards, coordinating with brokers, and negotiating rates.
• Deadhead miles: Without a streamlined process for securing backhauls, Sharp frequently ran empty trucks on return trips, incurring unpaid mileage and wasted resources.
• Limited scalability and decision-making resources: With limited resources to dynamically evaluate and prioritize backhaul opportunities, Sharp’s process was constrained by human limitations, leading to missed revenue potential and suboptimal fleet utilization.

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Solution

Boon introduced an AI Load Sourcing Agent to revolutionize Sharp’s backhaul and load sourcing operations. This AI-powered “worker” autonomously managed complex workflows, transforming Sharp’s backhaul strategy by reducing empty miles and maximizing operational efficiency. Acting as a digital team member, the AI agent demonstrated decision-making capabilities traditionally requiring human expertise, delivering results in real time. Key features of the solution included:

• AI backhaul sourcing: Proactively identifying and displaying profitable backhaul opportunities by seamlessly integrating with digital load boards, analyzing available loads, and prioritizing high-value matches.
• Automated collaboration: Once the backhaul selection is made, the agent automates the booking and confirmation process to eliminate time-intensive manual interactions.
• Integration with Truckstop: Leveraging real-time loadboard data from Truckstop to expand load sourcing capabilities, ensuring Sharp accesses a broader range of profitable opportunities.

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By incorporating this agentic AI worker into their team, Sharp not only automated repetitive tasks but also enhanced their operational intelligence, empowering the company to make smarter, faster decisions and achieve unparalleled efficiency.

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Results

The introduction of Boon’s AI Load Sourcing Agent delivered measurable and transformative results for Sharp:

• Increased revenue opportunity: By autonomously sourcing backhauls for return trips, the AI Load Sourcing Agent recommends over $5,000,000 in potential bookings annually and Sharp Transportation books an estimated amount of $170,000 via Boon’s load sourcing and backhaul recommendations. 
• Time savings: Load sourcing time decreased by 10 hours per week, as the AI worker continuously analyzed opportunities in real time, allowing Sharp’s human team to focus on strategic growth initiatives.

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By embedding an AI-driven team member into their operations, Sharp achieved a new level of efficiency and profitability, redefining their backhaul strategy for sustained growth.

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Conclusion

By integrating Boon’s AI Load Sourcing Agent, Sharp transformed its backhaul and load sourcing operations, achieving increased levels of efficiency, scalability, and profitability. The AI-powered solution served as a digital team member, autonomously managing tasks that previously required extensive manual effort, such as sourcing and prioritizing profitable backhauls.

With the AI seamlessly embedded into their logistics workflow, Sharp drastically reduced deadhead miles, maximized fleet utilization, and empowered their human team to focus on strategic priorities. The real-time decision-making capabilities of the AI worker not only streamlined operations but also enabled Sharp to scale their backhaul processes without increasing overhead.