ChristopherAI AE and PC Detection
Making sense of Unstructured Data
It doesn't matter if you have audio recordings of calls, emails, files, eMIRFs or web requests. There is a significant amount of information stored as unstructured data that can contain valuable information for your organization. ChristopherAI can evaluate any unstructured data and determine what the intent was for the interaction, whether there was an Adverse Event or Product Complaint or whether the question was answered properly. This means QA processes not only can be applied to 100% of the cases the company handles, but efficiency and accuracy is greatly improved.
Key Features
It doesn't matter if you have audio recordings of calls, emails, files, eMIRFs or web requests. There is a significant amount of information stored as unstructured data that can contain valuable information for your organization. ChristopherAI can evaluate any unstructured data and determine what the intent was for the interaction, whether there was an Adverse Event or Product Complaint or whether the question was answered properly. This means QA processes not only can be applied to 100% of the cases the company handles, but efficiency and accuracy is greatly improved.
Key Features
- AI enabled Natural Language Processing (NLP) to identify potential Adverse Events (AE) and Product Complaints (PC) in unstructured text content
- Identify and differentiate between drug products AE and combination products for appropriate processing
- Create and route E2B R3 appropriate files to the Argus or ArisG system
- Allow for the categorization and routing of combination products by a specialist
