Top 15 Real-Life NLP Applications for Businesses in 2025

Top 15 NLP Applications for Your Business

1. Chatbots

Chatbots are a popular conversational AI application powered by NLP. Facebook’s automated chatbots and Salesforce’s Einstein Assistant are typical examples of these tools.

With advanced technologies and NLP, chatbots can understand customer queries, retrieve relevant information, and provide real-time answers. For example, when a customer wants to view past transactions, NLP-powered financial assistants like Bank of America’s Erica can provide all transaction details across accounts.

Chatbots are available 24/7 to handle simple, common tasks on behalf of your business. They can collect customer data and even suggest personalized offerings. For more complex or unresolved cases, they can route the conversations to appropriate human agents without requiring customers to repeat all the information they already gave. This both keeps customers engaged and reduces waiting time.

2. Email Classification & Filtering

Have you ever wondered why Gmail can classify your emails into different tabs (e.g., Primary, Social, and Promotions) accurately? The answer lies in NLP and machine learning algorithms. With these technologies, the system can read each email, understand its intent, and put it in the most relevant folder. Updates from social networks, for example, go to Social, while advertisements or deals are sorted into Promotions. This will help you stay organized and save time in finding what you need.

Further, NLP helps prioritize important messages by analyzing such factors as sender information, keywords, or urgency. This ensures that critical emails don’t get lost in a crowded inbox, whether they’re urgent updates from colleagues or client requirements.

Another benefit of NLP in email management is spam filtering. By identifying keywords and patterns related to spam, NLP enables email systems to detect suspicious content, flag emails as spam, and automatically relocate them to a separate category. This function protects you from unwanted messages and even phishing attacks.

3. Search Results

With NLP, search engines like Google or Bing can understand the intent and even context behind your search query. Instead of just matching keywords, NLP algorithms can consider such factors as related terms or your search history to suggest more relevant results, even when your query is vague, complex, or grammatically incorrect.

Plus, NLP allows search engines to analyze the content of web pages and retrieve the most relevant information to generate concise snippets. Google and Bing now even integrate their generative AI assistants to return deep results based on your queries. Both snippets and deep results summarize what you’re looking for without the need to click through links.

Besides search engines, eCommerce sites also leverage NLP to benefit their search functionality. When you search for “comfortable office chairs” on Amazon, for example, NLP will consider “comfortable” as a crucial feature. It then identifies this keyword and other relevant terms (e.g., ergonomic, high-density foam, or supportive) within reviews and product descriptions to suggest products with high comfort ratings.

4. Data Analysis

NLP, coupled with machine learning algorithms, is changing how businesses process text data. This data, whether structured or unstructured, comes from different sources like internal reports, customer reviews, surveys, and social media posts. By extracting meaningful insights from this data, NLP can discover patterns that might be overlooked through manual analysis.

One visible application of NLP in data analysis is topic modeling. This technique can detect key topics or themes from massive volumes of data. For this reason, your company can easily identify common issues or requests within thousands of customer feedback entries. This insight helps your business solve customer concerns instantly and improve services accordingly.

Plus, NLP-powered models support tracking trends in big data. By interpreting and analyzing customer preferences and market shifts, NLP allows your company to identify changes in customer behaviors early, address possible problems before they arise, and adapt to evolving demands.

5. Sentiment Analysis

Imagine your brand is launching a new line of running shoes. How can you know whether people feel positive, negative, or neutral about the product line? While tracking each opinion or review manually on different platforms proves time-wasting and ineffective, many businesses now leverage sentiment analysis to gauge public opinion.

Sentiment analysis is one of the common NLP applications. It uses NLP and other advanced techniques (e.g., ML algorithms like Random Forests or Naive Bayes) to capture linguistic patterns, identify potential emotions, and classify text data. This text data can come from different sources like customer reviews, feedback forms, surveys, or social media posts.

For instance, when customers review your new product on sites like Google or Amazon, NLP can scan these reviews. It then looks for keywords, phrases, and tones that signal certain sentiments. If customers complain about the product’s quality (e.g., “uncomfortable,” “painful,” or “worst”), NLP can signal negative emotions. This allows your business to determine where to focus improvements.

6. Voice Recognition

Voice recognition is on the rise, with a 23.7% annual growth rate estimated from 2024 to 2032. This technology refers to the ability of machines to understand and respond to voice commands. Advancements in NLP, ML, and ASR (Automated Speech Recognition), coupled with big data, have escalated the capability of handling voice to a new level.

By interpreting natural language and analyzing user intents, various NLP-powered models can respond appropriately to voice commands. Such smart assistants and applications as Apple’s Siri or Google Voice can perform some tasks on human behalf, like looking up information, setting reminders, or scheduling meetings.

Another crucial use of voice recognition is transcription. In fields like media, law, or medicine, professionals can leverage NLP-powered transcription tools to note down spoken words faster. Voice recognition software such as Dragon by Nuance or Braina can listen to recorded audio or real-time voice and transcribe it into text with high accuracy. This saves time and effort while keeping written documents precise, especially in the context of lengthy legal proceedings.

7. Interactive Voice Response (IVR) Systems

IVR is an interactive phone system technology that uses both touch-tone (keypad) and voice recognition inputs to automate call handling. With NLP, IVR can greet callers, ask what service they want, and respond or direct calls accordingly based on their responses.

Many companies now use IVR for routine customer support in call centers, like banking services. For instance, when a caller says “I’d like to check my recent transactions,” NLP helps the IVR system recognize “recent transactions” as the keyword. Accordingly, the system can offer the details or route the caller to the right department or human agent.

This self-service capability speeds up and facilitates customer service while providing a seamless experience to customers. Also, this automation reduces the workload for human agents and enables them to focus on more complex issues.

8. Information Extraction

information extraction - nlp application

Information extraction is a crucial NLP application that automatically spots and retrieves information from unstructured text (like emails, articles, or legal documents). This retrieved information is then organized into structured categories, making it easier for further analytics, search, and other NLP applications like question answering or text summarization.

Accordingly, machines leverage multiple NLP techniques to interpret the underlying meaning and context of the text, which is crucial for effective information extraction. For example, they may use named entity recognition (NER) to determine and categorize named entities (like people or locations) within the text while relationship extraction is helpful for identifying relationships between entities (like “Google acquired YouTube).

With these NLP techniques, your business can save much time and effort retrieving data from vast datasets for different purposes. For instance, NLP systems can help your customer support teams retrieve common issues from thousands of customer feedback and reviews or support your legal teams to identify relevant information from piles of legal documents.

9. Predictive Text and Autocomplete

When you type “thank” on your iPhone’s screen, the keyboard then suggests “you” to help you complete the phrase quickly. Is this scenario familiar to you? This is often known as “predictive text” or “autocomplete” – the real-time assistance that keeps your communication faster and smoother while minimizing typing errors.

Another popular example of predictive text is Gmail’s Smart Compose. When you draft an email, this functionality will suggest phrases or words to complete your sentences with just one click. For example, if you type “If you have any question, please,” Gmail will recommend “let me know.”

By leveraging NLP techniques, these email systems and smartphone keyboards can analyze patterns and common phrases to anticipate what you can say next. These tools don’t only look at individual words but try to interpret context to offer better suggestions in real-time.

10. Grammar & Spell Checkers

Other key NLP applications are grammar and spell checkers. You might often see these tools in Microsoft Word and Google Docs. Whenever you type something, these tools automatically highlight misspelled words or incorrect grammar and then suggest real-time corrections. By capturing and fixing errors quickly, these tools can keep your writing clean and professional.

AI-powered tools such as Grammarly upgrade writing to new heights. They don’t just flag lexical or grammatical errors. But they also suggest ways to paraphrase sentences, indicate awkward structures, and provide better synonyms based on your writing’s intended audience and formality. This functionality helps you express ideas more clearly and improve your writing skills over time.

So, how can these tools do so? With the support of NLP and other AI technologies, grammar and spell checkers can analyze word choice, sentence structure, and context to detect inappropriate areas that need improvement. In business settings, these tools prove helpful in creating high-quality content, minimizing errors, and making clearer, more impactful communication.

11. Language Translation

Many language translation tools use NLP to convert text and speech from one language to another easily.

Take Google Translate as an example. The tool depends heavily on Neural Machine Translation (NMT) powered by NLP and other advanced technologies (e.g., deep learning with attention mechanism) to understand human language content and even its intent.

With this capability, the tool doesn’t only translate individual words, but also focuses on the content’s entire context to create an impressive translation at an impressive speed. The tool also learns from user inputs over time and enhances its translation capabilities over time to produce more accurate results.

Messaging apps and social media platforms are also transforming the way we communicate globally. Facebook Messenger, WhatsApp, and WeChat all offer a real-time translation feature that enables users to chat in different languages smoothly. This functionality allows for fast, natural conversations, be it for business or personal use.

12. Text Summarization

Have you ever imagined a powerful assistant who can summarize lengthy documents in seconds? Today, this dream comes true with the emergence of AI technologies, typically NLP. By identifying and retrieving the main points, NLP can turn extensive text or speech into clear, concise summaries that are both coherent and meaningful.

With text summarization tools like ChatGPT or Gemini, you can absorb important information without reading every detail, especially when you need to stay updated on numerous topics but have limited time. These tools allow your business to make quick, informed decisions while increasing productivity.

13. Natural Language Generation (NLG)

One advanced application of NLP is to produce natural language content. Tools like ChatGPT or Gemini can interpret human prompts, extract relevant information from their massive training data, and craft human-like, logical content.

For example, when we ask Gemini, “What is Conversational AI?” the tool returns a detailed answer that includes conversational AI’s definition, key components, use cases, and benefits. Instead of just listing facts, Gemini pulls data from different sources, analyzes it, and creates well-structured yet engaging content. This content creation process not only saves time but also ensures quality.

With this capability, NLG tools are widely used for various business tasks. For instance, marketing teams can leverage these tools to produce personalized email responses based on a customer’s profile and query. Meanwhile, financial departments can generate monthly reports to communicate complex data effectively.

14. Fraud Detection

Along with machine learning algorithms, NLP can help your business spot deceptive behavior by analyzing language patterns. In particular, it’ll study how language is utilized in emails, transaction details, or claims. It then compares the language used to training data and captures subtle signals that indicate security risks.

In the banking and insurance industries, for example, NLP can scan words and phrases to detect inconsistencies or exaggerations (e.g., “the loss was devastating…”) that point out high fraud potential. By discovering these red flags early, NLP can hinder fraudulent payouts and ensure the creditability of claims.

Social media platforms are now fertile playgrounds to approach your existing and potential audience. Indeed, one survey indicated that 94.5% of internet users are leveraging social networking sites. This has encouraged many businesses to monitor their social media regularly to stay updated about brand perception and public sentiment. Therefore, NLP comes into play to support them with effective social media management.

With NLP, you can take prompt action when someone talks about your brand on Facebook, Twitter, or Instagram. Whether this action is about thanking a loyal customer or handling a complaint, it shows your genuine care for the customer’s feedback, consequently fostering your online presence.

Further, NLP can analyze hot topics, keywords, and hashtags on social media to identify trends early. For example, when a certain product or service is suddenly mentioned in numerous posts, NLP can capture this trend and allow your business to create timely content that aligns with your audience.

Transform Your Business With Designveloper’s NLP Solutions

Through our article, we expect you to have a comprehensive overview of NLP applications for businesses. With advancements in AI technologies, NLP-powered tools will become more intelligent, streamlining various business tasks and freeing up human agents on complex, strategic initiatives. If you want to build a customized, scalable NLP solution, partnering with Designveloper is a good investment!

Since its foundation in 2013, Designveloper has built an expert team that specializes in software and AI development services. With extensive expertise and experience, we’ve crafted effective solutions that fit our clients’ business requirements.

One of our successful projects is Song Nhi. This is a virtual financial assistant that uses advanced tech like natural language processing or optical character recognition to help users manage their incomes and expenses easily.

Here at Designveloper, we offer the following AI development services:

AI Software Development: Our team utilizes the latest AI advancements to develop robust and scalable software applications that boost efficiency and your business growth.

Generative AI: By exploiting the power of advanced algorithms, we develop innovative and dynamic solutions that meet your unique business needs. Our solutions help your business make full use of GenAI to create engaging content.

AI Chatbot Integration: Our experts revolutionize your customer experience by smoothly incorporating AI chatbots into your existing platforms. Accordingly, your teams don’t need to conduct repetitive tasks that can delay their communication processes.

Besides these advanced technologies, we leverage Agile methodologies for NLP app development. With such Agile frameworks as SCRUM and Kanban, we can focus on the most important functionalities of your app, ensuring timely delivery to market and within budget. So do you want to further discuss your NLP idea? Contact us now!