What is RIOKEE?
An AI-powered platform optimized with Machine Learning used for creating hyper-personalized, predictive, and adaptive customer experiences as a driver for accelerating the go-to-market cycle of ideas affecting the life, physical, and engineering sciences.
What can you expect?
Quantifiable reduction in cost and time for taking products from ideas to market through an Omni-product marketplace using AI-powered workflow analysis.
Current go-to-market strategies in the life sciences will need to be swift, forcing them to adopt new technologies at a never-before-seen pace. In order for Biotechs and Pharma to adjust, legacy R&D pipeline models will have to shift to be human-centered, automated, and AI-enabled.
What People Are Saying
“In an autonomous era, companies will produce products at or nearer to the source of consumption. In this new autonomous reality, items would be available to customers on-demand and in real-time by accessing the flow of intellectual property and production when needed and producing products in seconds”.
– Glenn Steinberg
EY Global and EY Americas Supply Chain Leader
“Companies that use data to gain a deep understanding of their customers and provide unique experiences will exponentially accelerate along the next S-curve of growth“
EY Global Innovation Realized Leader and EY Americas Advisory Growth Strategy Leader
A different type of Biotechnology Company
Originality: One of today’s challenges is being able to successfully fuse Science and Technology to offer a robust R&D platform. Ambrosia wants to bring the ability to do research and development to the 15-35-year-old demographic. We hope that by putting research capabilities in the hands of the masses, we can exponentially increase the amount of experimental data collected and help propel humanity to new heights of intellectual development in a shorter amount of time.
Innovation: A digital platform where you can align all the logistics of complex R&D operations into a production funnel and eventually create a tangible output. Whether it is a prototype, an experimental data set, or a complex formulation. You will find everything you need with pay as you go or subscription-based pricing. By using AI and Machine learning we want to build the blueprint for various experimental design workflows and create user personas around them. By obtaining this data and integrating it with our AI and machine learning component. We hope to create a highly customizable and intuitive UI/UX, scientific virtual assistants, and spot-on product offerings.
Feasibility: The industry leaders usually only ruminate under one scientific industry. No one has been able to fuse R&D for the life, physical, and engineering industries under one single point. The technologies needed for this are already well defined but clustered within a defined industrial segment with significant barriers of entry for individual users. We aim to capitalize on cloud architecture and create a user experience that will allow all teams and individuals alike to be able to centralize R&D operations at scale.
Sustainability: By selling services, physical and digital products we ensure that we have maneuverability in the tangible and intangible markets. Therefore, hedging risk against the volatility of demand for either type of product or service.