Inven Extract+Effortlessly extract meaningful entities
In today’s data-driven world, industries spanning diverse sectors are increasingly recognizing the crucial need for a robust Document Classifier and Entity Recognizer to efficiently process and analyze vast amounts of unstructured data, enabling them to unlock valuable insights and enhance decision-making processes.
Inven Extract+ is a document classifier and entity recognizer with an NER-based extraction tool that uses natural language processing (NLP) to automatically identify and extract entities from unstructured data. It’s designed to save the organisation’s time by automating the entity extraction process.
- Accurate entity extraction with 95 % accuracy
- Automates entity extraction, saving 40% of time
A hospital can use the application to extract relevant information from medical reports such as patient names, ages, medical conditions, and medications. For example, in the Cath report case, we can extract information such as ejection fraction, WBC count, platelet count, and more.
A company can use the application to extract specific entities from customer service emails or chat logs such as customer names, order numbers, and product names. This can help customer service representatives quickly identify and resolve customer issues.
A company’s HR department can use the application to extract specific entities such as employee names, job titles, and relevant dates from employee resumes. This can help the HR department identify qualified candidates and streamline the recruitment process.
The Insurance company can leverage this product to streamline claims processing by automating entity extraction from unstructured data, enhancing efficiency, and improving accuracy in document classification and information retrieval.