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RunBot A.I.

Unlock the Future of Automotive Shipping

Streamline transportation logistics and unlock unparalleled efficiency with RunBuggy’s Generative A.I. system

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See RunBot A.I. in Action

Intelligent Workflow Optimization

RunBot, an advanced generative AI system, is fully integrated with RunBuggy’s cutting-edge transportation management platform. Together, they streamline the automotive shipping process, transforming logistics into a finely tuned orchestration. Every step, from stakeholder coordination to on-time delivery, is meticulously managed, ensuring a seamless shipping journey.

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Enhanced Experience, Reduced Overhead

RunBot’s proficiency leads to a significantly better experience for shippers and a notable reduction in operational costs. Utilizing data-driven insights, the system autonomously resolves 85% of orders, minimizing the need for manual intervention. For complex cases, RunBot offers invaluable support, enhancing decision-making with its predictive capabilities.

AI-Powered Operations Support

RunBot prioritizes tasks and predicts delivery challenges with an 80% accuracy rate. It strategically identifies transport stress points and facilitates optimal transporter assignments, considering routes, capacity, and performance. This AI-guided sourcing not only boosts transporter earnings and expedites shipping but also contributes to environmental goals by reducing empty mileage.

Automating for Efficiency

The AI system substantially decreases manual operations. Sourcing efficiencies are directly channeled into the RunBuggy platform, enabling automatic outreach to the best-matched transporters. By integrating driver ratings, the system enhances accountability and expedites order movement, addressing potential delays proactively.

LLM’s Business-Wide Impact

RunBot leverages large language models, like ChatGPT, to bring unparalleled clarity to the transportation network. It interprets complex requirements and conversations, avoiding logistical missteps and enhancing operational efficiency. RunBot also simplifies user interaction with the software, significantly reducing the learning curve.

RunBot, powered by a wealth of data from RunBuggy’s digital marketplace, drives unprecedented efficiency and reliability in automotive transportation. By harnessing comprehensive data—from software integrations to GPS tracking—it ensures the success of all stakeholders involved. Welcome to the future of car shipping: intelligent, integrated, and ready for success.

Dr. Patrick Weinkam

Dr. Patrick Weinkam

Head of Data Science

Patrick has spent 15 years working on applied data science problems. Prior to RunBuggy, he architected and built a virtual assistant platform for automotive technicians, where he was co-founder and CTO. He previously served as a consultant to various data science software companies and was also lead data scientist for an enterprise data center company that was acquired for $1.3 billion. In academia, he worked with Pfizer and UC San Francisco on cutting edge drug design projects where he developed servers used throughout the scientific community. He received his Ph.D. from UC San Diego and B.S. from UC Santa Barbara.
Dr. David Erickson

Dr. David Erickson

Principal Data Scientist

David Erickson is a Principal Data Scientist at RunBuggy. He has consulted for Cash App, Facebook, and Levi’s. A former CTO, he has a strong quantitative background with a PhD in Physics and BS degrees in Math and Physics. He enjoys working on complex problems like transportation logistics and marketplace dynamics.
Chris Wang

Chris Wang

Senior Data Scientist

Chris Wang joined the data science team at RunBuggy in May 2022. He has worked on a variety of projects related to task management, fraud detection, building data extraction pipelines for external vendor, etc. More recently he has been a part off the core RunBot team.

Prior to joining RunBuggy, Chris worked for SOFI, Intuit and GE in data science related roles. He has done a variety of work in fields such as recommendation systems, A/B testing, natural language processing, graph mining, fraud detection, etc.

Chris has dual bachelor's degrees in Math and Physics from University of California, Irvine and a Master's degree in Statistics from Columbia University.

Raymond Chen

Raymond Chen

Operations Data Analyst

My name is Raymond Chen, and I currently serve as an Operations Data Analyst at RunBuggy. I graduated from California Polytechnic State University in San Luis Obispo, majoring in Business Administration with a focus on Information Systems. Analyzing data, optimizing operational processes, and crafting visualizations to bring data to life are aspects of my role that I truly enjoy. In my free time, I have a passion for snowboarding, exploring new places, trying out diverse cuisines and beverages, and delving into their intriguing histories.
Pat Blachly

Pat Blachly

Data Science Consultant

Pat is a Data Science Consultant for Runbuggy. Prior to joining the team and helping to build RunBot, he led data initiatives and scaled Data Science and Analytics teams at companies in the legal tech (Ontra AI) and digital health (Doximity; IPO’d in 2021) spaces and received a Ph.D. in Chemistry from UCSD working on computer-aided drug design.
Millie Lantz

Millie Lantz

AI Decision Support Sr Manager

Millie is an AI Decision Support Sr Manager at RunBuggy. Prior to joining the Data Science team, she was an Operations Manager at RunBuggy focusing on B2B Enterprise accounts. Millie's previous experience is at the executive level of automotive dealership management. She enjoys problem solving, and the synergy and collaboration of working within the team.

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