Converting text into knowledge

Advanced solution for extraction, analysis and classification of unstructured textual information by Melingo. Extracting insights and knowledge out of free text using an advanced NLP and Machine Learning  technology. Get your free demo!

    ?how it works

    Recognizes entities from a wide world of concepts

    This capability is based on advanced language analysis tools and machine learning technologies that allow to extract the main entities out of free text, such as: names, locations, offensive terms, id’s, weapon, time expressions etc.


    A natural-language ability that connects via API to the client’s operational processes (such as call centers and Omni channels platforms) and helps the organization to classify customers’ applications and calls to the right department/persons.

    Sentiment Analysis and CUSTUMER service insights

    A machine learning solution that helps to extract sentiment automatically out of free text. The solution can handle multiple sentiments in the same paragraph while being able to split properly between positive and negative sentiments and their related domains. The solution also enables to extract customers satisfaction, service quality and communication insights out of discussions with customers.

    extracting insights from open text surveys

    Morfix Insights can identify the main topics and entities in the survey text and sort them into structured categories automatically. Insights could be: complaints topic and segmentation, abandonment risk, important details on competitors and their offering.

    ?2What can be done with Morfix Insights

    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.

    ?Who can benefit

    Morfix Insights can help any organization that seeks to transform raw text to structured data, for example:

    Financial institutes

    Retail chains

    Healthcare services

    Insurance companies

    Call centers

    Companies and service providers in the fields of request customer satisfaction analysis

    Security and intelligence institutions

    Contact us to get additional information and demo

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