Artificial intelligence has immense economic promise, but there is a lot of work actually applying AI to jobs in the real economy. AI Valiot is a company that develops AI solutions for major manufacturers, where even marginal efficiency improvements add up to major savings.
We asked Valiot CEO Federico Crespo about this company and the growing role of AI in manufacturing.
Tell us a little of yourself and Valiot
Sure, my name is Federico Crespo. I am the CEO of the operations/manufacturing AI Valiot. We manage artificial intelligence for major suppliers like Heineken, John Deere, Metalsa, and more. From a young age I was exposed to inefficiencies within the manufacturing industry.
How has Heneken’s manufacturing benefited from Valiot
In the Summer of 2021, Heineken became the first major manufacturer to implement Valiot, and with incredible results. Since starting their partnership with Valiot, Heineken has reported a 25% Cycle Reduction Time, 17 % In Process Inventory Reduction, and a 5% Throughput Brewery Increase. Valiot’s data monitors assured BBT and filtration time were reduced in all cycles. Brewing capacity also increased significantly per month. The migration to digital has enabled Heineken México to have a real-time visualization of the bottling lines and filtering conditions in each batch.
What excites you about the future of AI
It’s super exciting to see all the capabilities that AI and robotics have. However, it’s a bit too early to know how these capabilities will develop in the next 10-20 years. AI is reminiscent of the early nineties of the internet, with infinite potential for growth, so it’s amazing to be part of it. It feels good to be present for these developments not just as a spectator, but also as a player.
What are some challenges you see for the future of AI
At the same time, there are certain concerns that remain about the future of AI. Access to education in math and computer science will have to be heavily expanded for people to remain competitive in the job market. In this sense, job extinction is a major concern. New technology evidently eliminates a lot of jobs, but it creates new, more productive jobs as well. In this light, it will be all the more important to invest in comprehensive coding education for children in order to reduce barriers to entry into this job market and get kids engaged in a time where people’s attention spans are shrinking.
How has Valiot changed the manufacturing industry?
We have proven false the notion that software is difficult to implement in an old school industry. In fact, AI-based software will likely be the key to keeping these industries relevant. Valiot recently spoke with Texas government officials about its potential to bolster statewide growth, reshoring, and Texas’s overall GDP. Connecting these two ecosystems is a unique opportunity that has the possibility for mutual benefit. Valiot’s team empowers factory operators to make use of the software independently, adjusting with little to no learning curve. Our approach is factory-friendly and time-saving across all industries.
How Could Valiot Change the World?
We are disrupting how operations are being executed in manufacturing facilities and providing AI capabilities to operators who haven’t even heard of AI in their lives. Our goal is to inspire growth not just for factories, but for their operators. We are transitioning away from how software companies used to implement new tech, which was extremely aggressive for factories and their employees. In addition, if you believe in free market competition, our tech is going to drastically reduce the cost of living for everyone. We’ll also reduce the carbon footprint from the manufacturing world.
How does Valiot implement Digital Twin Technology?
Valiot’s product ValueChainOS uses and analyses data from different sources to simulate value chain conditions. This helps companies better understand their production requirements and create actionable items regarding what and when to buy, produce, and more importantly, when to change. For example, they were able to help a chemical factory reduce costs and optimize inventory balance via the systems’ Smart Scheduler and Digital Twin interface. Using the digital twin allows owners to understand and predict how the factory is going to behave, and identify problems before they occur. Not only are production cycle times, manufacturing costs, and utility consumption all drastically reduced, but the UX of the application allows for clear and real-time communication between stakeholders.
Peter Page is the Contributions Editor at Grit Daily. Formerly at Entrepreneur.com, he began his journalism career as a newspaper reporter long before print journalism had even heard of the internet, much less realized it would demolish the industry. The years he worked a police reporter are a big influence on his world view to this day. Page has some degree of expertise in environmental policy, the energy economy, ecosystem dynamics, the anthropology of urban gangs, the workings of civil and criminal courts, politics, the machinations of government, and the art of crystallizing thought in writing.