our capabilities

Natural Language Processing (NLP)

Discover how we've helped our client's achieve business transformation since 2004

Semantic similarity

Semantic Similarity, also known as Semantic Textual Similarity, is a job in Natural Language Processing (NLP) that analyses numerous sentence structures to find similarities between them using a specified metric.
Keyword/ Key phrase extraction

The objective of keyword extraction is to automatically identify terms that best describe the content of a document. In Text Mining, Information Retrieval, and Natural Language Processing, keyword extraction is a critical problem.
Emotions / Sentiment analysis

Sentiment analysis is text mining that finds and extracts subjective information from source material, allowing a company to better understand the social sentiment of its brand, product, or service while monitoring online conversations.
Entity Extraction

It allows machines to recognize and extract entities such as product names, events, and locations automatically. Search engines use it to analyses queries, chatbots use it to communicate with humans, and teams use it to automate time-consuming processes like data input.
Topic Modeling

Topic models can help us organize and analyses massive volumes of unstructured text bodies by providing insights. It's a statistical model for identifying the abstract "topics" that appear in a set of documents.

Uncover deep insights from structured and unstructured data, by understanding NLP techniques

Unlock the real potential of data, that helps your business to gain a competitive advantage with natural language processing. Imagine all the unstructured content that can generate significant business insights after data processing - it could be email communications, videos, enquiries, customer reviews and feedbacks, support requests, online publications, or social media interactions. Our natural language processing techniques allows businesses to perform compliance monitoring and analysis of structured, semi-structured or unstructured content. By training your system with NLP techniques, you can reduce a great amount of manual work involved in text analysis and semantic processing of speech and text.

Our Natural Language Processing Solution helps you with:

Processing huge amounts of structured and unstructured data
Semantic Analysis of Unstructured Content to derive insights
Identifying emotions behind speech through sentiment analysis
Finding the most pertinent information from large databases
Improving accuracy and efficiency of documentation process

Use Cases

Customer Services

Our NLP techniques help in automatic processing of customer service requests, customer calls, and other interactions such as reviews or feedbacks shared by the customer. The system self-learns to map the new words to existing patterns or creates new patterns as appropriate. Our natural language processing solution supports use cases such as email response management, case management, and knowledge management.
Legal Industry

Legal professionals can make informed-decisions quickly through data processing by discovering key insights hidden inside huge volumes of information. Text mining and text analysis techniques support in building strategies that can often change the trends or course of cases. Natural language processing helps in contract management, information retrieval, and article summarization.
Healthcare

Enhance the accuracy of electronic health records by translating free text into standardized data with Zerone’s NLP techniques. Healthcare experts can manage the risks associated with chronic diseases with more intelligently with predictive analytics. Our data processing units can summarize insights from massive volumes of medical or health publications and identifying expert care givers in less time.