Natural language Processing

4 business applications for NLP

Though NLP seems like a new technology in the current trends, many businesses have been harnessing its phenomenal value for a long time. In fact, you also experience NLP on a daily basis without even knowing it. The spell-check on your phone, the online search and many other features of the modern technology have been possible due to the advancement of NLP.

NLP or Natural Language Processing allows the machines to understand a language like humans. When an actual person looks for an information, he or she tries to use certain keywords. Those keywords take the person to a particular set of informational documents. The same idea is used in machine learning. The NLP technology makes it easier for machines to act like humans and search information to understand the language.

In the world of business, NLP has attained an essential place and this article shows the most popular business applications of NLP.


Chatbots are the newest forms of NLP applications. The chatbots make communication possible between actual human and machine. In the beginning, they were incorporated just to create a better experience for consumers. For instance, people can write “burgers” and a chatbot of a burger company would take the order. However, the chatbots have now become valuable for B2B along with the B2C sales.

Many startups have already leveraged chatbot technology in their HR department, employee management, and others. These upgrades have allowed businesses to manage a smooth workforce functionality in their companies.

Neural MT or machine translation

In the beginning, machine translation wasn’t very good in terms of accuracy. However, the machine learning technology of NLP has allowed software to grow with time. The technology makes it possible for the software to learn words and create a vast storage with time. As a result, the machine starts understanding languages with time just like a child does. However, the accuracy of the machine translation depends on the number of words and the time provided to the machine.

Neural machine translation is a step further in the same direction, which reduces the required time to a great level. Now, businesses don’t have to wait for too long in order to get a grown-up software. The first neural machine translation was launched in 2016 by Microsoft. With that, many other software tools came into the picture such as Amazon Translate and Google Translate.

Conversation-driven search

Going beyond the chatbots, the conversation driven searches are now possible for businesses. For instance, a software called Second Mind listens to all the business meetings on an ongoing basis. During a meeting, this software can use the phrases used in the conversation and find out potential results.

Hiring via tools

The hiring process has become much easier for managers and recruiters. The candidate search tools are using the search technologies to find out candidates who fit the job profile. This has reduced the cost and the chances of mistakes at the same time.

The use of natural language is changing how machines work and interact with humans. And these 4 use cases depict that NLP is set to grow at a massive pace in the next few years.


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