Serkanto AI
Discover the benefits your product needs to stand out
Serkanto AI is a platform designed to rapidly identify and validate bioactive RNAs in medicinal plants, fungi, and fresh foods, leveraging advanced artificial intelligence (AI) technologies. At its core, it employs machine learning and deep learning algorithms to uncover dietary RNAs that can boost the efficacy of natural ingredients, transforming the process of identifying and developing scientifically backed natural solutions with enhanced speed and precision.
A comprehensive research and development process
Kresko's platform follows a research and development process divided into several key stages:
Prediction:
Serkanto-AI is powered by groundbreaking discoveries from our scientific team, who have unlocked the mechanism behind natural bioactive RNA production. It compiles biological data on the RNA cargo of dozens of superfoods and botanicals after simulating oral ingestion or topical application conditions. This information is integrated with multi-omic data derived from decades of research in plant biology, RNA science, and biomedical studies, allowing us to build digital models that connect dietary RNAs with human health outcomes.
Leveraging cutting-edge AI, we can accurately predict which specimens will yield dietary RNAs to support specific wellness needs such as tissue regeneration, immune support, or digestive wellness, significantly reducing the need for extensive experimental testing.
Biological Validation:
Candidate compounds are subjected to laboratory testing through assays developed by the research team, allowing the experimental validation of model predictions before advancing to commercial development. This validation ensures that final products are backed by solid science and meet our safety and effectiveness standards.
Kresko's cell-based assay platform stands out for its speed, versatility, and reliability. With over 20 validated assays already established across key well-being categories—including digestive function, tissue regeneration, immune support, stress response, energy metabolism, and detoxification—our platform enables rapid innovation tailored to the food, supplement, and cosmetics sectors. Thanks to its advanced infrastructure, we can develop new assays in under 30 days and deliver accurate results with minimal technical errors or contamination in an average of just two weeks.
Production:
We transform our discoveries into bioactive ingredients, ready for application in various industries. At the core of this stage is our proprietary RNA stabilization technology, which uses an exclusive buffer made entirely of natural food-grade ingredients, free from synthetic chemicals. This sustainable approach requires minimal feedstock, preserving the original integrity of the source material—"we preserve what was there in the first place." Our production process is both environmentally friendly and highly cost-effective and scalable, featuring streamlined manufacturing protocols that minimize direct labor and capital expenditures. Additionally, all our products are protected by robust intellectual property, ensuring their market differentiation and value.
Machine Learning and Deep Learning: The technological foundation of Serkanto
Machine learning and deep learning are the key technologies driving our platform. Each plays a crucial role at different stages of the process:
Machine Learning:
We use machine learning to process data from medicinal plants and fresh food samples from high-throughput sequencing experiments. This enables us to identify and understand which RNAs are bioactive in each plant, unlocking insights into their biological roles and potential applications.
Deep Learning:
Our deep learning models enable us to uncover complex, non-linear relationships between bioactive compounds and their effects on human biology. This flexibility allows us to refine predictions and optimize outcomes by experimenting with advanced neural network architectures. We also use deep learning to analyze phytochemical and genetic data from plants, predicting which laboratory assays are most likely to yield meaningful results. This allows us to efficiently prioritize resources and uncover bioactive with the highest potential for health applications
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