In a previous interview with WeAreAquaculture, Aquaticode's CEO, Stian Rognlid, said that while the aquaculture industry has come a long way, there is still a long way to go, noting the important role that artificial intelligence (AI) will play in that process. The company is taking the first step on that path by officially launching for production its AI-powered SORTpro solution, designed to sort up to 10,000 juvenile salmon per hour based on gender and other performance traits.
Before this launch, Aquaticode's solution, capable of identifying gender in juvenile salmon through non-invasive methods, has been evaluated over time and at scale by Chilean producer Salmones Camanchaca. The results, which the company has described as "innovative," show a verified gender classification accuracy of more than 97% and no increase in mortality rates.
Currently, manual ultrasonic operators sort about 100 million fish per year in Chile, a method that has been shown to promote faster growth of male and female batches compared to mixed groups. Aquaticode's system automates this procedure. In doing so, it not only improves flexibility, efficiency, and accuracy but also extends gender sorting capabilities to regions where such practices were previously not carried out due to the high labor costs involved.
Chile was therefore an ideal place to test the efficiency of the SORTpro AI-based solution. "Camanchaca, who historically sorts around 15 million fish per year, has given us invaluable support in bringing our solution to the market," claims Aquaticode’s CEO, Stian Rognlid. "We appreciate their openness in sharing their facilities and expertise with us".
Aquaticode and Camanchaca's R&D collaboration dates back to 2021. They started with the development of a first proof of concept along with the manual sorting process, but over the years, Camanchaca's contributions have led to highly accurate classifications not only in gender - where, as mentioned, a verified figure of over 97% has been achieved - but also in early sexual maturation and deformities.
"Innovation is central to our strategy at Camanchaca," explains Carlos Soto, Head of R&D at the Chilean salmon producer. "Artificial intelligence is emerging as one of the most promising megatrends in food production. We are quick to support initiatives that can lead to more efficient and sustainable salmon farming."
In the interview mentioned above, Stian Rognlid said that the combination of AI and automation will be a force of change in the aquaculture industry and added that in this industry, it is not a question of "if" and "to what degree" it will happen, but "how fast." The launch of this solution for production is Aquaticode's first step in developing the potential for AI in the aquaculture industry, but the company's ambitions go further.
"The SORTpro is a platform. In the near to medium term, we will introduce functionality to identify additional fish growth, health, and robustness traits. Each of these will bring significant value to farmers, but we truly believe that the sum is even greater than the parts," Aquaticode's CEO explains.
Backed by Nacre Capital, a venture builder for AI within the life sciences, Aquaticode raised a USD 6 million Series A in 2022. This was its first external fundraising round with the goal of accelerating projects to detect, identify, and predict relevant performance traits across multiple marine species.
The company's advisory board includes notable figures in aquaculture, such as former Cargill Aqua Nutrition CEO Einar Wathne, now Chairman at the NCE Seafood Innovation Cluster. "It was easy to get behind Aquaticode’s mission," reflects Einar Wathne. "Making decisions based on individual fish analysis and acting in real-time is the future of salmon farming. It's about growing better fish as well as growing fish better."
Founded in 2018 by Nacre Capital, and formed by an international team of entrepreneurs, inventors, researchers, technologists, and industry thought leaders, Aquaticode is a leader in the blue food revolution and a reference innovation partner in multiple aquatic species value chains. Its AI is based on deep learning infrastructure and has been trained to predict fish and shrimp phenotypes through machine vision.
