Automated requests tagging can help refer the request to the right place with no need for manual sorting, thus saving time and human resources. This can also be used for automatic replies according to the identified subject.

Classification of transcribed requests into subjects can optimize the calls manageשment: easier search of calls according to their subject, identifying the subjects that appear most often, etc.

Identification of sentiment  in social media or any organizational data can help measuring  your customers and audience sentiment on a certain topic, product, idea, etc.

Classification of email or other ways of contact requests can help create fast and accurate automatic replies or refer the request automatically to the right department.

Free text fields in medical documents can contain valuable information about the diagnosis or recommendations for follow-up treatment. Conversion of these texts into structured data can make the treatment process more efficient and accurate and save precious time.

Entity extraction can be used to identify keywords such as skills, professions, companies, degrees and more from a candidate's resumé and from the job opening and match them to determine how well the candidate fits for the job.

Free language bots can be a useful tool for easy and fast communication, and they require understanding the intent of the text (what the person meant). Morfix Insights can help identify the intent in the free text, while correcting typos, understanding slang phrases and splitting the sentence to more than one intent, if needed.

Extraction of entities from the texts according to the customer's needs for further classification of drill down. Morfix Insights contains dozens of built-in entity types, such as names, dates, locations, phone numbers, medical terms and many more, and also can extract user-defined entities that are specific for the project.