Top trends of
Natural language processing

Natural Language Processing (NLP) bridges the communication gap between computers and humans by bringing together advanced Artificial Intelligence, computer science, and linguistics.NLP enhances computer-human interaction by giving computers the capability to interpret human languages, both text, and speech.

By 2027, the Market value of NLP will be $61.03 Billion with a CAGR of 26.60%.
Will be 14 times larger in 2025 comparing 2017
More than 52% of organizations are using NLP powered applications
1 in 4 businesses are planning to adopt NLP
77% of business users lack trust in their data
50% of IT budget may be spent on rework and information scrap

Benefits of NLP for enterprises

Improves customer experience

Streamlines business operations

Simplifies mission-critical processes

Increases business performance.

Reduces costs and inefficiencies

What can NLP do?

All AI-powered tools have NLP. Most virtual assistants we use today, like chatbots and voice assistants, are fueled by NLP. The interpreting capability of NLP has opened doors for its use across multiple industries and various purposes. It can find a text, analyze it, interpret it, and respond both in text and speech. NLP has a wide range of capabilities which include

Chatbots and Voice Assistants
Search results
Email filters
Predictive text
Sentiment analysis
Language translation

Digital phone calls
Data analysis
Text analytics
Text summarization
Spam detection
Information extraction

To know more about NLP

Top trends of NLP

1. Repurpose NLP

With transfer learning, a machine learning approach, you can repurpose NLP for any related activity, avoiding developing and training a model from scratch, saving time and money.

2. Mass Data analysis

With NLP, analyzing documents and extracting information can be simplified. This will reduce enterprises’ workforce, time, and effort on lengthy documents.

3. Intelligent Chatbots

Intelligent chatbots can automate customer support processes as they do not rely on rules or keywords like rules-based algorithms chatbots. They offer a highly specialized and customized experience.

4. Enhanced enterprise collaboration

Generally, organizations involve multiple parties in decision-making. It can be challenging to track and analyze everyone’s input. With NLP, the voice recording devices can extract context and provide information to make better business decisions.

5. Cyberbullying detection

As cyberbullying has increased, it is essential to detect and prevent it. You can use NLP to detect cyberbullying by creating classifiers on social media or other platforms to identify abusive and insulting language and hate speech.

6. Fake news detection

NLP can detect fake use using NLU, which classifies misinformation and true information.

7. Social media monitoring

NLP can monitor social media using sentiment analysis. Marketers can now use NLP to analyze the impact of their marketing campaigns and evaluate the customer behavior to their new product launches or events and what customers feel about their brand.

8. Workplace sentiment analysis

NLP can help employers gain real-time insights into employees’ feelings about work and their organization. With the gained insights, employers can impose new policies to improve employee satisfaction and retain them for a long time.

9. Multi-lingual NLP

With the advent of language agnostic sentence embeddings and zero-shot learning, companies like Google and Facebook are increasingly building multi-lingual pre-trained models along with mono-lingual models benefiting all language people.

Why choose SAXON?

We incorporate advanced NLP in our solutions to provide our customers with intelligent solutions that will give them the best results and nothing less. Our intelligent solutions are enriched with NLP to understand the context of the text, provide the best responses, extract accurate information, and provide better analysis and classification.
Our intelligent solutions: