Worlds

Worlds is building the enterprise platform for real-world AI. Our software brings AI-based Automation directly into the physical operations of the world's largest industrial companies. Companies like Chevron, Werner Industries, and Timken Steel are all using Worlds today to measure, analyze, and build AI-based automation into their physical operations at scale. Worlds is creating AI as infrastructure and bringing AI and automation to the base layer of new organizational structure. Our new software, WorldsNQ is flipping the entire AI training industry from a top-down, human-in-the-loop process to a bottom-up, fully automated AI system. For the first time ever, organizations can convert the data from their existing cameras and sensors into a live data stream that they can use to measure and build AI-based automation directly into their physical operations. WorldsNQ is a completely unsupervised AI that is more accurate, more comprehensive, and 100X faster than any current market solution. AI training projects that take 3-6 months to complete today are done in hours with NQ.

To date, there has not been a way for large organizations to measure and improve their real-world environment. Our focus is on large industrial companies in the center of the supply chain, primarily manufacturing, distribution, and logistics, helping them solve their most difficult operational problems. As these large industrials are growing larger and faster than they ever have before, their ability to observe, analyze, affect, and de-risk operations at scale has become untenable. Compounding the problem are narrow-point solutions, and they are everywhere- mostly computer vision companies, Digital twin providers, or sensor companies all making claims that, even if they were true, address only a tiny sliver of a much larger problem. What’s really needed is one place where they can all come together (cameras, sensors, AI, people processes) and that’s exactly what we have built with the Worlds platform. We have spoken with Digital Transformation teams all over the world and what we’ e been told consistently is that what they want is consolidation.