Shield AI is an artificial intelligence company founded in 2015 with the mission to protect service members and civilians with intelligent systems. The company’s Hivemind autonomy stack is the first and only autonomous AI Pilot, deployed in combat since 2018. Hivemind enables intelligent teams of aircraft to perform missions ranging from room clearance to penetrating air defense systems, and dogfighting F-16s. Backed by top-tier Silicon Valley VC funds, Shield AI has established itself as the leader in AI for aviation. Shield AI has been named to Forbes’ AI 50 and Best Startups lists, CB Insights Top 100 AI Companies, and Fast Company’s Most Innovative Companies. The company has offices and facilities in San Diego, Dallas, Washington, D.C., and Abu Dhabi.
Stack AV operates in the transportation industry that develops advanced autonomous systems. Stack's autonomous technology integrates state-of-the-art advancements in artificial intelligence, robotics, machine learning, and cloud technologies. This integration empowers us to develop groundbreaking solutions tailored to the evolving demands and obstacles within the trucking industry.
Cruise is innovating in the field of autonomous vehicles, focusing on creating self-driving technology that safely connects people with their desired destinations. Operating in complex urban environments like San Francisco, Cruise aims to enhance transportation by exposing its vehicles to the same challenging scenarios that human drivers encounter daily.
ClearQuote is an innovative app that leverages smartphone images and artificial intelligence to automate vehicle inspections. By allowing leasing companies to efficiently track the external condition of vehicles, it enhances the customer experience during handovers and streamlines processes for insurers, ultimately saving time and costs in underwriting and claims processing.
Helm.ai develops AI software for driver assistance systems, autonomous driving, and robotics. Autonomous vehicle developers often rely on a combination of simulation and on-road testing, along with reams of datasets that have been annotated by humans, to train and improve the so-called “brain” of the self-driving vehicle. Helm.ai's software expedites the timeline and reduces costs; that lower cost also makes it particularly useful for advanced driver assistance systems. Helm.ai uses an unsupervised learning approach to develop software that can train neural networks without the need for large-scale fleet data, simulation, or annotation. The software is also agnostic to whatever compute and sensors are used in the vehicle, allowing Helm.ai to pitch to a diverse set of customers.