Aquabyte, a startup that uses computer vision and machine learning models to optimize fish farming efficiency, today announced a $3.5 million seed round of funding co-led by Costanoa Ventures and New Enterprise Associates (NEA), with participation from Princeton University and other strategic U.S. and Norwegian investors.
Aquabyte’s technology will augment the visual IQ of human-operated systems by collecting data with underwater 3D cameras. The cameras are installed in fish farm pens, where they follow fish and determine the size of their biomass to calculate optimal feed quantity. Through the application of machine learning algorithms, Aquabyte anticipates that this more efficient feeding could result in as much as a 20 to 30 percent decrease in feed cost during a fish’s lifetime, which could save tens of billions of dollars.