#StartupsEverywhere: Annie Lu, CEO and Co-Founder, Laminar
This profile is part of #StartupsEverywhere, an ongoing series highlighting startup leaders in ecosystems across the country. This interview has been edited for length, content, and clarity.
Third Generation Manufacturers Changing the Industrial Landscape
After witnessing the 2022 baby formula crisis, founder and CEO Annie Lu joined her brother in starting their Physical AI company, Laminar. They help process manufacturers ensure sustainable production of their products through real-time chemical data from their sensors and AI models they’ve created. We sat down with Annie to discuss her company, the importance of protective patents, and Laminar’s emphasis on providing sustainable processes to customers.
Tell us about your background. What led you to Laminar?
Growing up on the factory floor as third generation manufacturers, my brother and I saw firsthand how critical manufacturing is to the modern day. It’s one of the most ubiquitous sectors in the world, and it’s consistently overlooked and chronically underfunded. That neglect was the cause of the infant formula shortage crisis in 2022 and led to needless death. My brother and I looked at this, and we started thinking about how we could build technology to help prevent another manufacturing crisis.
What is the work you all are doing at Laminar?
The manufacturing industry largely consists of two types of processes: discrete manufacturing, assembling components for electronics or vehicles, and process manufacturing, converting raw materials into products such as pharmaceuticals or food. Process manufacturing, our focus, involves a worker periodically sampling and lab testing the product undergoing chemical reactions. The key gap is that manufacturers can't know the quality of their product beyond the moment when the product is tested manually. We were pushed towards our service by the fundamental data and context gap with AI in manufacturing.
At Laminar, we developed our own proprietary sensors that physically attach to pipes and other production equipment throughout the production line. These sensors collect chemical data on the quality of their blend. Our reasoning models use the data to assess and implement the needed adjustments with no human loop. We call this real-time monitoring Process-Aware Autonomy. It’s not just about efficiency, though. We help our customers prevent recalls by providing quality, safety, and sustainability.
How does your technology help increase manufacturing capacity?
Our work with our partners is meant to complement their human workforce while enabling them to unlock additional value. Right now, there’s an ongoing loss of skilled labor in the industry as experienced factory workers retire or will retire in the next three to five years. Those workers might have 20 years experience and that inherent expertise is largely leaving with them. In fact, many of our customers have around 40 percent of their shop floor operators with less than one year of experience. Many worry about Laminar replacing jobs, yet there are barely enough people to fill the currently available manufacturing roles. This is the case across the United States and various regions across the world, and our product helps reduce the impact of the expertise gap.
Additionally, changing markets have led to explosive growth in manufacturing systems. 10 years ago, one of our clients produced four stock keeping units (SKUs). Now, the same client produces 300 different SKUs on the same legacy infrastructure, demanding increased agility as they switch between different products. Instead of replacing workers, manufacturers need to develop technology that works for the factory floor workers as the processes advance.
Have you pursued intellectual property protection for your hardware, software, and processes?
We have patents on our hardware, software methodology, and beyond. Making sure that we’re protected and hold the rights to our proprietary technology is important for our business security. We're very fortunate to be working with some incredible patent attorneys since it’s not uncommon for individuals to attempt to benefit from the intellectual property gaps. Defensibility is important for startups like Laminar that are innovating and bringing their products to market.
Why is hardwired connectivity often the preferred option in manufacturing environments?
In manufacturing, our customers prefer hardwired connectivity for a couple of reasons. First latency is critical because conditions and operations can change by the second. We need to be running communications—and the reasoning—at very high speeds. Second, wired connectivity provides greater reliability and fidelity in communications. In manufacturing environments, there is often significant electromagnetic interference from the large amount of equipment in use, so our customers actually prefer wired communications. Industrial manufacturing requires highly reliable, accurate, and robust technology.
Are there any local, state, or federal startup issues that you think should receive more attention from policymakers?
Water policy and industrial efficiency need to be part of the same conversation. In food and beverage manufacturing, significant amounts of water are consumed during cleaning cycles that often still run on decades-old static timers. With the help of physical AI, facilities could save millions of gallons by using only the water they actually need.
What are your goals for Laminar moving forward?
Process-Aware Autonomy becomes the standard operating model for every process manufacturing facility in the world, and every production line runs as a self-driving factory.
All of the information in this profile was accurate at the date and time of publication.
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