Enversion A/S was founded in 2009. We develop AI-assisted healthcare and AI-powered accounting automation to design, build and implement decision support systems dedicated to the healthcare and finance sectors in Denmark. Currently, we help Danish regions process huge amounts of healthcare data from electronic health records, laboratory systems, patient administrative systems, etc. Besides we help larger organizations optimize internal procedures by automating accounting and procurement processes. We secure that knowledge becomes easily available to all decision-makers for them to make the best decision in a given situation, at a given time. Our growth strategy is aggressive, and our main focus is to create intelligent AI solutions for data-driven decision-making. Our toolbox contains the newest data science techniques: Machine learning, data mining, text mining, and operations research. Every day we go to work with our mission in mind: To deliver the market's smartest data solutions and use data to make the world a better place – because we can!
Enversion’s value chain is the foundation in our work and our solutions dedicated to the healthcare and finance sectors. The value chain consists of four steps:
Data is king. Without enough data, our AI solutions do not make sense. Therefore, the Data Center is the foundation and the first step in our working process. The Data Center is established to access the data needed to solve the client’s issue(s).
The second step, the Fact Center, is a datawarehouse algorithm that integrates all relevant data from the particular operational systems. The purpose of this second step is to process, clean, integrate, and quality assure data preparing it for further analysis.
The third step, the Analysis Center, uses data collected in the Data Center and processed in the Fact Center, as input to the construction of the algorithms for decision support. The third step is where data begins adding noticeable value for the consumers through the data-driven decision support systems. About what and within which field the algorithms should support the experts in their decision-making, depends on the data delivered as input in the first two steps.
The fourth step, the Value Center, ensures that the algorithms for decision support, built in the third step, are embedded in the working procedures and thereby create true value for money. This can be done by integrating knowledge from the algorithms in any system already used by the client, like EHR systems or any financial systems.
Enversion A/S is the IT provider in the CDSS project. The project is a clinical decision support system that, using artificial intelligence, will help health professionals in municipalities and hospitals identify citizens at risk of emergency hospitalization. We are inventing the artificial intelligence and machine learning tools to be used in the project. Learn more
A digital assistant has been trained to recognize patterns based on historical behavior in The North Denmark Region invoice management. Every night, the digital assistant assesses all invoices from that day, which leaves the client with: - Many human resources released to be used elsewhere - An overall quality of the posting that has been significantly increased - A solution that makes sure that far more incidents of accidental double and error billing are captured. Learn more
Many larger organizations spend lots of resources negotiating favorable procurement agreements. Agreements that are not necessarily being met by all of the organization's employees. Our digital assistant, Eia, will alert all employees to the existing procurement agreements when he or she uses Google or any other search features online or within an internal system to search for a product or service to purchase. Learn more
During the next five years, Enversion will work closely with some of Denmark's best medical doctors and researchers in the field of breast cancer, to develop and build a dynamic knowledge bank. Enversion will make use of machine learning and artificial intelligence in the creation of the knowledge bank, which will ultimately support doctors and therapists in predicting, treating and preventing late effects of breast cancer treatment. Learn more