When knowledge grows and changes rapidly and training data is not optimized in medical domains, it can be difficult to create NLP solutions that accurately identify and extract relevant concepts. NLP vendors often lack the necessary experience to deal with the complexity of clinical and biomedical language, account for nuances, and identify relationships between words and phrases. In addition, solutions built on open-source NLP models often require significant investment to add the necessary domain expertise.