The 6 Best Keyword Extraction Tools & How to Use Them

Keyword extraction uses machine learning and artificial intelligence to automatically “read” texts (news articles, social media, emails, online chats, etc.) and extract pre-defined or relevant words. 

This technology helps businesses automatically comb through product reviews, customer service tickets, and surveys, among other data, to understand important keywords and extract key information (like names, emails, values).

While you can infinitely customize open-source tools, you’ll need a sizeable computer science background to build your own extractor. The easiest and most efficient way to start using keyword extraction is often with SaaS tools that you can simply plugin and start using right away. 

Read on to learn about some of the best online keyword extraction tools.

Keyword Extraction Tools

Learn more about each tool to help make your decision. Many even offer free trials and models, so you can plug in your data and see how it works.


Best for: Companies that want to analyze customer and visualize data for immediate insight.

MonkeyLearn is an easy-to-use SaaS platform that allows you to perform keyword extraction on any data source, right away. You can customize your own extractor or use this pre-trained model to see how keyword extraction works. 

If you want to perform keyword extraction then visualize the results, explore MonkeyLearn Studio. This all-in-one text analysis and data visualization suite allows you to choose from business templates, custom-designed for each use case.

Each template combines extraction and classification models to give you super granular results. You also have the option to build your own keyword extractor. Once you’ve decided on your template and task, just upload your data and MonkeyLearn will do the rest.

And don’t worry if you’re new to machine learning. MonkeyLearn’s intuitive point and click interface is accessible to everyone. And extraction tools can easily be integrated with applications you already use, like Google Sheets, Excel, Zendesk, Zapier, and more.

For those who know how to code there’s, MonkeyLearn API. Otherwise, explore MonkeyLearn Studio

IBM Watson

Best for: Big companies with internal engineering abilities that want to extract keywords from text and speech-to-text from huge amounts of data. 

IBM Watson offers a number of tools for text analysis built to scale across industries. With their Natural Language Classifier you can build simple extraction models by uploading CSV files. Their cloud technology offers easy implementation with existing applications, though advanced integration will require coding expertise.

IBM Watson’s Speech-to-Text automatically turns audio to text, in real time, and is ideal for companies with large call centers and recorded audio feedback.

Amazon Comprehend

Best for: Companies that want managed software, with no building requirements.

Amazon Comprehend is fully managed software, working on Amazon Web Services’ cloud, so there is no internal installation required. Their pre-trained APIs integrate directly into your existing systems, or they can build custom extractors for specific needs. 

Amazon Comprehend’s machine learning programs scour text for relationships that human users may be unable to find. Comprehend AutoML can be used to build custom models and extractors, although no coding is required.

Amazon Comprehend Medical is a favorite among medical professionals to identify and find relationships within medical information, like conditions, medications, and dosages. Put to use on exams, trials, and health records, Comprehend Medical can improve diagnoses and save lives.


Best for: Companies that want easy set-up of fixed APIs.

AYLIEN offers three API plug-ins with easy set-up in seven major programming languages.

AYLIEN’s News API allows you to real-time search and analyze thousands of daily news sources from around the world. Their Text Analysis API is a premade keyword extraction program for analyzing text data from documents and online content. And finally, their Text Analysis Platform enables you to build your own text analysis extractor (right in your browser) for ultra-targeted results.

Best for: Companies that want quick implementation and low-level supervision. uses a neuroscience-based method to search, extract, and analyze keywords from nearly any unstructured text. Their models can be trained quickly with vocabulary specific to your field, without the need for human supervision.

Their software creates a “semantic fingerprint” to represent the meaning of a text as a whole. Semantic fingerprints visualize your data, showing keyword clusters and how they relate to each other. offers a pre-packaged Message Intelligence software/hardware combo for customer service and related messaging analysis. Contract Intelligence is generally for statistical and business insight evaluation, and Custom Solutions provides AI that’s tailor-made to your requirements.


Best for: Businesses that need a number of customization tools, like multiple models trained for various specialized searches.

TextRazor can be integrated in the cloud, or self-hosted for added security. Their keyword extraction techniques work in 12 languages, with extraction built to show word relations, typed word dependencies, and synonyms. 

TextRazor’s machine learning is built with advanced semantic parsing and understands context, to read text as a human would. Use custom, domain-specific logic and build custom classification rules for advanced analytics. APIs can be integrated in minutes with just a few lines of code.

Final Words on Keyword Extraction Software

Keyword extraction can help your business increase productivity, improve customer service, and help you stay in touch with your customer base. 

Once you’ve uncovered keywords, your data can be coupled with other text analysis tools that help you classify texts by sentiment, topic, language, and more.

There are a number of online extraction tools you can use to take advantage of this groundbreaking technology.

Want to give keyword extraction a try? Request a demo from MonkeyLearn.

Rachel Wolff

Rachel Wolff

BA in journalism and French from Sheffield University. Interested in human-machine collaboration and Google's ever-changing algorithms.


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