Jun 8, 2023

10 Best NLP Optimization Tools in 2023

Suman Samal, Asst. Marketing Manager
Suman Samal
10 Best NLP Optimization Tools in 2023
Suman Samal, Asst. Marketing Manager
Suman Samal
Jun 8, 2023

10 Best NLP Optimization Tools in 2023

Discover the best NLP optimization tools in 2023, designed to enhance language processing and improve business operations. Learn more on our blog.
10 Best NLP Optimization Tools in 2023

Table of contents

Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on understanding and processing human language. NLP optimization tools enable businesses to analyze unstructured text data from various sources like emails, social media posts, customer reviews, and much more. These tools help organizations extract valuable insights, automate tasks, and improve decision-making processes.

In 2024, several NLP optimization tools will be available to help businesses tackle their language processing needs. This blog post will discuss the top 10 NLP optimization tools in the market today, their features, benefits, pricing, and factors to consider when choosing the right tool for your use case.

#1. Scalenut NLP Analysis Tool

Scalenut home page - a good choice for an SEO Clarity Alternative

Scalenut is an AI-powered SEO and content marketing platform that helps users plan, research, create, and optimize content in one place. It features natural language processing (NLP) analysis, which is a technique that enables machines to understand and generate human language. NLP analysis allows you to produce more effective and engaging content with a human-like tone and style. It also improves the readability and SEO performance of the content by using relevant keywords, phrases, and topics that match the user’s intent and the search engine’s expectations.

Key Features

  • NLP Optimization: Find semantic keywords that help the search engine understand the context of your content and improve the overall comprehensiveness of your piece.
  • Topic Discovery: Identify captivating topics ideas (keywords) with high search volume and low competition that resonate with readers.
  • AI-powered Content Generation: Leverage AI capabilities to automatically generate NLP-optimized content, including blogs, marketing copies, social media posts, and more, based on user input and preferences.
  • Enhanced SEO Success: Maximize SEO effectiveness by analyzing content structure, content depth, keyword density, and more while receiving valuable suggestions for improvement.
  • Content Clustering: Build content clusters that establish topical authority and drive organic traffic to your website.


  • Essential: $39/mo 
  • Growth: $79/mo 
  • Pro: $149/mo 

#2. Google Cloud Natural Language API

Google Natural Language API home page 

Google Cloud Natural Language API is a powerful NLP tool that allows developers to analyze text data and extract insights using Google's machine learning technology. The API supports various programming languages, including Java, Python, Node.js, and more. It offers a RESTful interface, making it easy to integrate into your applications.To use the Google Cloud Natural Language API, you need to create a project on the Google Cloud Platform, enable the Natural Language API, and obtain the required credentials. You can then make API calls to perform natural language processing tasks on your text data.‍

The API provides several pre-trained models to perform tasks such as:

  • Sentiment Analysis: It can analyze the sentiment of a given text, determining whether it is positive, negative, or neutral.
  • Entity Recognition: It identifies and categorizes entities within a text, such as people, organizations, locations, events, and more.
  • Entity Sentiment Analysis: This feature goes beyond entity recognition and provides additional information about the sentiment associated with each recognized entity in the text.
  •  Syntax Analysis: It parses the structure of sentences and extracts information such as parts of speech, grammatical relationships, and syntactic dependencies.
  • A subscription-based pricing model

#3. IBM Watson NLP

 IBM Watson NLP home page 

IBM Watson NLP is a suite of AI services that offers Natural Language Understanding, which helps businesses identify and extract keywords, categories, emotions, entities, and more from text data. The platform is versatile, with the ability to tailor its services to different industries, including healthcare and finance.

  • Domain customization: You can train Watson to understand the language of your business and extract customized insights with Watson Knowledge Studio. This allows you to create custom models that suit your specific domain and use cases.
  • Text analytics: You can use text analytics to extract categories, classification, entities, keywords, sentiment, emotion, relations, syntax, and more from your text data. These features can help you surface real-time actionable insights, improve search and discovery, and automate workflows.
  • Deploy anywhere: You can deploy Watson NLU behind your firewall or on any cloud. This gives you flexibility and control over your data and infrastructure.
  • In addition to Watson NLU, IBM also offers the Watson NLP Library for Embed, which is a containerized library for IBM partners to integrate in their commercial applications. The library provides common NLP features, such as:
  • Sentiment analysis: You can classify text to positive, negative, and neutral sentiment. This can help you understand the opinions and emotions of your customers, users, or stakeholders.
  • Entity extraction: You can detect and extract named entities such as personally identifiable information (PII), locations, dates, organizations, and more. This can help you protect sensitive data, enrich your content, and perform analytics.
  • Text classification: You can label any given text and assign it to a specific category or group. This can help you organize your data, filter out irrelevant content, and perform targeted actions.

A subscription-based pricing model

#4. SpaCy

SpaCy home page 

SpaCy is a popular open-source Python library for advanced NLP tasks, known for its speed and accuracy. It is designed to support large volumes of data and comes with pre-trained models and word vectors.

  • Multi-task learning with pre-trained transformers like BERT.
  • Pretrained word vectors and embeddings.
  • Production-ready training system and easy model packaging, deployment, and workflow management.
  • Linguistically-motivated tokenization.
  • Components for named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking, and more.

It is a free tool.

#5. MonkeyLearn

Moneylearn home page 

MonkeyLearn is a user-friendly NLP platform that helps businesses gain valuable insights from text data. The platform allows users to perform text analysis tasks such as sentiment analysis, topic classification, and keyword extraction. MonkeyLearn also provides users with the ability to build customized machine-learning models tailored to their specific needs.

  • Instant data visualizations and detailed insights with an all-in-one text analysis and data visualization studio
  • Pre-built and custom machine learning models for various text analysis tasks, such as sentiment analysis, topic classification, entity extraction, etc.
  • Business templates for different scenarios and data types, equipped with pre-made models and dashboards
  • Easy integration with your apps and BI tools using native integrations, SQL connection, or API
  • Customizable machine learning models

#6. TextBlob

TextBlob is a Python library built on top of NLTK (Natural Language Toolkit), offering a more intuitive and user-friendly interface for common NLP tasks. It is an excellent choice for beginners looking to tackle NLP tasks like sentiment analysis, text classification, part-of-speech tagging, and more. 

  • Sentiment analysis
  • Text classification
  • Part-of-speech tagging
  • Phrase extraction
  • Word and phrase frequencies
  • Parsing
  • Word inflection and lemmatization
  • Spelling correction
  • WordNet integration
  • Add new models or languages through extensions

#7. Amazon Comprehend

Amazon Comprehend is an NLP service integrated with the Amazon Web Services infrastructure. This API allows users to perform NLP tasks such as sentiment analysis, topic modeling, entity recognition, and more. For healthcare professionals, Amazon offers Comprehend Medical, a specialized variant for advanced analysis of medical data.

Amazon Comprehend examines the following categories of insights:

  • Entities - Mentions of individuals, locations, objects, or places found within a text.
  • Key phrases - Phrases that are present in a document.
  • Personally Identifiable Information (PII) - Personal data that can be used to identify an individual, such as addresses, phone numbers, or bank account numbers.
  • Language - The primary language used in a document.
  • Sentiment - The prevailing emotional tone of a document, categorized as positive, neutral, negative, or a combination.
  • Targeted sentiment - The sentiments associated with particular entities mentioned in a document.
  • Syntax - The grammatical structure and parts of speech for each word in a text.
  • Document clustering (topic modeling) - The capability to group documents based on common themes or topics.
  • Custom classification - The ability to train a model to categorize documents according to your own defined categories.
  • Custom entity recognition - The capacity to train a model to identify domain-specific terms or phrases tailored to your specific needs.

It has a pay-as-you-go pricing model.

#8. NLTK

NLTK (Natural Language Toolkit) is a Python library designed for the processing of textual data. It offers user-friendly interfaces to more than 50 corpora and lexical resources, including WordNet. 

  • Tokenization
  • Filtering stop words
  • Stemming
  • Tagging parts of speech
  • Lemmatization
  • Chunking
  • Chinking: Removing words from a chunk that do not belong.
  • Named entity recognition
  • Concordance
  • Dispersion plot
  • Frequency distribution
  • Collocations

#9. AllenNLP

 AllenNLP home page 

AllenNLP is a powerful research-focused NLP library backed by the Allen Institute for Artificial Intelligence. Built on top of the popular PyTorch deep learning framework, AllenNLP provides automated modules for essential deep learning tasks, making it a great choice for researchers and developers.

  • Preprocessing
  • Model training and evaluation
  • Model serving
  • Visualization

#10. GenSim

GenSim is a state-of-the-art Python library for topic modelling and text similarity analysis. It is designed for large-scale text processing, offering fast, scalable, and efficient handling of large text files. GenSim uses unsupervised models, eliminating the need for costly annotations or hand tagging of documents.

  • Topic modeling
  • Text similarity analysis
  • Efficient handling of large text files
  • Unsupervised models

#11. Stanford CoreNLP

Stanford CoreNLP is a robust and fast toolkit for NLP developed by the NLP community at Stanford University. Written in Java, it features APIs in most programming languages and provides scalability and speed optimization.

  • Parts-of-speech tagging
  • Tokenization
  • Named entity recognition
  • Dependency parsing

NLP (Natural Language Processing) optimization tools can offer several benefits to businesses. Here are some ways in which NLP optimization tools can help businesses:

  • Improved customer support: NLP tools can analyze customer interactions, such as emails, chat logs, or social media messages, to extract valuable insights. This helps businesses understand customer sentiments, identify common issues, and provide more effective and personalized support.
  • Efficient information retrieval: NLP optimization tools can enhance search engines and recommendation systems. By understanding the context and intent behind user queries, businesses can deliver more accurate and relevant search results, leading to improved user experience and increased conversions.
  • Sentiment analysis and brand monitoring: NLP tools can analyze social media posts, online reviews, and other text sources to gauge public sentiment towards a brand or product. This information allows businesses to identify potential issues, monitor brand reputation, and take proactive measures to address customer concerns.
  • Automated content analysis: NLP tools can process and analyze large volumes of text data, enabling businesses to extract valuable insights quickly. This can be useful for market research, competitor analysis, trend identification, and content curation, helping businesses make informed decisions and stay competitive. 
  • Compliance and risk management: NLP optimization tools can aid in compliance monitoring by automatically analyzing documents, contracts, and regulatory texts. They can identify potential risks, flag non-compliant content, and help businesses ensure adherence to legal and regulatory requirements.
  • Data extraction and knowledge management: NLP tools can extract structured information from unstructured text, making it easier to organize and manage data. Businesses can use these tools to automate data entry, extract key information from documents, and build knowledge bases for improved decision-making and data-driven insights.
  • Language translation and localization: NLP optimization tools can assist businesses in translating and localizing content across different languages. This facilitates global expansion, enables effective communication with international audiences, and opens up new markets.

Overall, NLP optimization tools help businesses streamline processes, gain valuable insights from text data, enhance customer experiences, and make informed decisions based on a deeper understanding of language and context.

Scalability and Integration

When choosing an NLP optimization tool, consider how well it can scale to handle the volume of data you need to process. Additionally, evaluate the ease of integration with your existing systems and applications.

Customization and Flexibility

The ability to customize the tool to meet your specific requirements is crucial. Look for tools that allow you to build custom models or modify existing ones to adapt to your business needs. Flexibility in terms of supported languages and functionalities is also an essential factor.

Security and Compliance

Ensure that the NLP optimization tool you choose complies with data privacy and security regulations relevant to your industry. The tool should provide robust security measures to protect your data and maintain compliance with applicable laws.


In summary, choosing the most suitable NLP optimization tool for your business involves considering key factors like scalability, integration, customization, flexibility, security, and compliance. By thoroughly evaluating the features, benefits, and pricing of the aforementioned top NLP tools, you can make an informed decision and select the tool that aligns best with your requirements. You can also sign up for a 7-day free trial with Scalenut and explore our NLP analysis feature to optimize your website and improve your ranking. 

Scalenut is an AI-powered SEO and content marketing platform that helps discover and create relevant content for your customers. Be it brainstorming a content strategy, creating comprehensive briefs, generating the content, or optimizing it per the best SEO practices, Scalenut has made the process extremely easy. Click here to create a free account and explore the many features of this tool.

Suman Samal
Asst. Marketing Manager
ABout the AUTHOR
Suman Samal
Asst. Marketing Manager

Suman Samal is a Asst. Marketing Manager at Scalenut. She is a technology enthusiast with a keen interest in content marketing and SEO. She truly believes that with the right set of tools every organization can improve the ROI of their content marketing campaigns. She spends her time managing content operations at Scalenut and ensuring that everything we publish is of the highest quality.

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