Fuel your AI with the highest quality data

Your AI engine can be trained more effectively when it can analyze data from multiple sources in a standardized model. The Coperor industry data model for healthcare ensures that the data feeding your AI engine will be aligned across sources, resulting in more reliable results and avoiding the much-feared hallucinations that can arise when data is taken out of context.

It’s critical to invest the time to grade the importance of content sources (“authority weighting”), which helps the model understand the relative value of different sources. This weighting is a core function of the Coperor Master Data Management (MDM) engine where sophisticated rules calculate the relative authority assigned to each data field within each system.

AI models rely on high-quality training data, and flaws like errors or inconsistencies can severely impact their performance. Poor data can lead to nonsensical outputs or deficiencies in generative models. Coperor ensures quality with automated validation pipelines, human review for nuanced errors, and continuous monitoring to address bias and maintain integrity.

Protecting user privacy, obtaining proper consent, and maintaining data confidentiality are non-negotiable ethical obligations when developing generative AI systems. Organizations must implement robust mechanisms to adhere to all relevant data privacy regulations like GDPR, CCPA, and HIPAA. This involves comprehensive de-identification and anonymization of any personal or sensitive data used for model training. Coperor provides robust access controls, encryption, and consent management for all healthcare data.