10x Cost Reduction

Enabling you to redeploy your workforce to critical tasks, particulary during COVID-19.

Process Optimization

Distributed network enabling agility, flexibility and optimization in your organization’s processes.

Rapid ROI

Faster cargo routing and tracking, removing all process delays, saving you time and money.

Ben was awarded the Fulbright Scholarship to pursue his research in autonomous robotics. He obtained his MS in Aeronautics and Astronautics from Stanford University. There he developed estimation algorithms for autonomous systems with the Stanford Intelligent Systems Lab. His technical background spans; optimal, non-linear and multi-robot control techniques, estimation, and real time artificial intelligence pipelines. Ben has over eight years of experience in the robotics industry developing production level software and algorithms, including multi-robot systems, drone racing, and autonomous driving. While attaining his Bachelors in Mechanical Engineering at University College Dublin, he developed simulation models to validate and test the Attitude Determination and Control System for the first Irish Satellite, EIRSAT-1, in collaboration with the European Space Agency.

Zach achieved his MS in Aeronautics and Astronautics at Stanford University, researching and developing autonomous Guidance, Navigation and Control (GNC) systems. There he conducted research at the Autonomous Systems Lab, where he developed optimal control software for flexible space robotics. After attaining his BS in Aerospace Engineering at University of Texas, Zach developed radio astronomy and digital signal processing software at the Space and Geophysics Applied Research Laboratory. He has over twelve years experience developing full stack autonomous systems and GNC software in both research and industry. His prior experience also includes design, development and validation of control software and simulation environments for the NASA iSAT Mission.

Kevin has over seven years of experience researching, developing, and deploying cutting edge hardware technology. He achieved his bachelor's degree in Electronic Engineering at University College Dublin (UCD), where his research thesis focused on the design and development of single-pixel synthetic aperture detection systems. As part of UCD's optical engineering laboratory team, he developed multiple industry funded optoelectronics projects. There he focused on simulation, modeling, and verification using real world hardware. He has also led the development and design of several production grade hardware projects for Fortune 500 companies and laboratories at UCD.

Byron brings a wide range of experience and wealth of knowledge from the safety critical industries, including, autonomous vehicles, medical device development, and aerospace design. After graduating from Santa Clara University in 2016, he began working at Space Systems Loral on structural design and analysis for hundred million dollar satellites. After working for two years in the aerospace industry, Byron chose to pursue a Master's degree at Stanford University, focusing on robotics controls and optimization. During his masters he interned at Ike, developing hardware and software for autonomous trucks. Byron graduated with his Masters in Mechanical Engineering from Stanford in 2020.

Mac Schwager is an assistant professor of Aeronautics and Astronautics at Stanford University. He directs the Multi-robot Systems Lab (MSL) where he studies distributed algorithms for control, perception, and learning in groups of robots and autonomous systems. His research interests include cooperative robotic manipulation, automated multi-robot manufacturing, multi-robot warehouse management, cooperative surveillance with teams of UAVs, autonomous driving in crowded urban and freeway environments, and autonomous drone racing. He obtained his BS degree from Stanford, and his MS and PhD degrees from MIT. He received the NSF CAREER award in 2014, the DARPA Young Faculty Award in 2018, and has received numerous best paper awards in conferences and journals including the IEEE Transactions on Robotics King-Sun Fu best paper award in 2016.

David Obershaw is a Lecturer in Stanford University’s Department of Electrical Engineering, where he teaches “Insanely Great Products: How do they get built?”. This course introduces the best product development practices from leaders in the field. With over forty years in the information technology industry, David has served in a wide range of leadership roles in marketing, product management, sales, and business development in both large and startup companies, including: IBM, Hewlett-Packard, MasPar, Red Pepper Software, PeopleSoft, and Proofpoint. He earned his MBA degree from Stanford Graduate School of Business, and BA degrees from UCLA. Previously, he served as president of the Board of Trustees at Charles Armstrong School (serving children with dyslexia and related learning differences).