MOA Foodtech debuts AI platform to convert byproducts into fermentation ingredients
MOA Foodtech has unveiled Albatros, an AI-powered microbiology platform that aims to transform fermentation processes across the food and feed sectors. The technology, launched from the company’s headquarters in Navarre, Spain, is designed to help manufacturers convert industry byproducts into commercially viable ingredients faster and more affordably.
The company claims Albatros can cut development timelines from six months to two weeks and reduce associated costs by 95%. By leveraging a proprietary microbiology dataset, the platform identifies optimal microbial strains and fermentation strategies to improve yield, functionality, and nutritional value.
“Using proprietary protocols, Albatros can analyse a microorganism’s DNA and predict its nutritional needs in just 10 minutes,” says Bosco Emparanza García, founder and CEO of MOA Foodtech. “This unlocks huge possibilities with fermentation, and it has the power to transform the food industry.”
The platform allows manufacturers to move away from traditional, high-cost inputs such as refined sugars, instead using food industry side-streams as feedstocks. MOA reports a 75% faster ingredient development timeline when using upcycled starches, with significant cost savings.
Albatros works by analysing data from a library of 200 food byproducts and matching them to suitable microbial processes. The platform then recommends targeted experiments, which MOA’s lab team executes to streamline R&D efforts.
MOA has also introduced a complementary service through its website. The tool allows manufacturers to submit details of their byproducts and receive a tailored assessment estimating their potential value when used in fermentation.
The company offers Albatros via a Microbiology-as-a-Service model, providing end-to-end support from feedstock selection to process optimisation. According to MOA, its approach has already helped convert waste streams into ingredients with revenue potential up to 20 times higher than conventional low-value applications.
