One System For Everything
Pluaris organizes all of your healthcare data into one system. You no longer have to go into 10 or more tools to find what the answers you need.
Doctors spend less time researching and finding the right medicines for their patients and more time with their patients.
Doctors, nurses, and staff are able to seamlessly share new medicines, clinical trials, procedure techniques, hospital protocols, and regulations across their organization.
Key Benefits of Pluaris
All-In-One AI Software
Pluaris provides Medical Staff, Doctors, and Specialists with the tools needed to benchmark medical guidelines, quickly identify the best treatment options for patients, and streamline administrative tasks. For Healthcare Providers this means reducing costs, increasing performance, and providing the best care to their patients.
Identification of Medicinal Products (IDMP)
The objective of the IDMP is to simplify the exchange of information for stakeholders, enhancing interoperability of systems in the EU and internationally. In parallel, the European Medicines Agency (EMA) is implementing messaging standards developed by HL7 (Health Level Seven). A large amount of change in documentation defining data elements and structures for unique identification and exchange of regulated information is required. Our AI Robot, Pluaris, has successfully demonstrated its capabilities.
In addition, we are looking to roll out Pluaris with a few non-profit organizations in healthcare. We expect Pluaris will generate value with its contextual data comprehension engine.
For example, assisting radiologists in providing timely inputs assessing MRI and CT Scans, healthcare providers decrease cost and gain operational efficiencies.
What does Pluaris Solve?
Today's Healthcare Problems
Let's get a bit technical
When we say sector agnostic, we mean it!
Unlike other AI solutions, our AI techniques were created to mimic the way humans interpret information. Pluaris breaks down every sentence into its grammatical components. This allows users to train machines with their domain expertise faster than competitive products.