Revolutionizing Medicine & Cleantech

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Our AI-driven platform accelerates all parts of the scientific workflow including literature review, hypothesis generation and ranking, experimental design & verification, both computational and physical, patent search and generation, writing and reviewing of papers, and scientific data analysis. We are beginning with a focus on medicine and clean energy but our platform can easily extend to other areas of science including chemistry, physics and materials science. 

We use the latest AI techniques and technologies to develop personalized treatments for patients based on their unique genetic makeup, lifestyle, and other factors. This approach leads to more effective treatments that have fewer side effects.

We work on codeveloping cell and gene therapies for a variety of diseases. We use AI cutting-edge technologies along with our partners to create therapies that have the potential to cure diseases that were once thought to be incurable.

We work on codeveloping therapies that stimulate the body's natural ability to heal itself. Together with or partners we codevelop approaches to  stem cell design and other innovative techniques to restore damaged tissues and organs.

We are working on codeveloping immunotherapies that harness the power of the immune system to fight cancer and other diseases. We use advanced techniques to create therapies that are more effective and less toxic than traditional treatments.

We work on codeveloping innovative drug design along with delivery systems that improve the efficacy and safety of drugs. Along with targeted drug discovery, we design advanced materials and techniques to create delivery systems that can target specific cells or tissues, and release precision drugs over a longer period of time.

AI algorithms can screen and simulate millions of potential new material combinations for solar cells and batteries in a fraction of the time it would take with traditional "trial and error" methods. This speeds up the discovery of promising new chemistries like advanced perovskite solar cells or solid-state battery electrolytes.

By analyzing vast datasets, machine learning models can accurately predict the performance, stability, and degradation of new materials before they are synthesized allowing researchers to focus on the most viable candidates, and eliminating unproductive avenues of research.

AI systems are used to fine-tune complex manufacturing variables—such as temperature, humidity, and chemical composition—for solar cell and battery production. This leads to higher yields, reduced waste, and more consistent product quality.

AI-powered systems can optimize battery charging and discharging cycles in real-time to extend a battery's lifespan and improve its performance. These systems analyze usage patterns and environmental conditions to proactively manage the battery's health and prevent degradation.