Top Natural Language Processing Companies 2022


As more and more firms undertake synthetic intelligence (AI) in quite lots of sectors, these AI are inevitably put in positions the place they have to interact with human beings. From customer assist chatbots to digital assistants like Amazon’s Alexa, these use cases necessitate educating an AI tips on how to hear, study, and perceive what humans are saying to it and the way to reply.

One method for teaching AI the method to communicate with humans is natural language processing (NLP). Sitting at the intersection at AI, computer science, and linguistics, natural language processing’s aim is to create or practice a computer able to not simply understanding the literal phrases humans say but additionally the contextual implications and nuances discovered of their language.

As the AI trade has grown in prominence, so too has the NLP trade. A report from Allied Market Research valued the worldwide NLP market at $11.1 billion in 2020, and it is anticipated to develop to $341.5 billion by 2030. Within that valuation lies a myriad of each promising startups and experienced tech veterans pushing the science additional and further.

History of Natural Language Processing

Natural language processing has been part of AI analysis because the field’s infancy. Alan Turing’s landmark paper Computer Machinery and Intelligence, in which the famous Turing Test was introduced, features a activity requiring the automated interpretation of pure language.

From the 1950s to the 1990s, NLP analysis largely centered on the symbolic NLP, which makes an attempt to teach computers language contexts by way of associative logic. Essentially, the AI is given a human-generated knowledge base designed to include the conceptual components of a language and the way these parts relate to at least one one other.

Using this data base, the AI can then perceive the meanings of phrases in context through IF-THEN logic. An instance of this would be similes. If you stated, “He’s as quick as a cheetah,” the AI would understand that the person you’re talking about would not be a literal cheetah.

Thanks to will increase in computing energy starting within the 1990s, machine learning algorithms had been introduced into natural language processing. This is when machine translation applications began gaining prominence. Examples you would possibly use can be Google Translate or DeepL.

As the web grew in popularity through the 2000s, NLP machines gained entry to much more raw data to sift via and understand. As such, researchers started focusing on creating unsupervised and semi-supervised learning algorithms. These algorithms had been much less accurate than supervised studying algorithms, but the sheer amount of data they processed can offset these inaccuracies.

Today, many natural language processing AIs use representational studying and deep neural network-style machine studying strategies to develop more accurate language modeling and parsing capabilities.

Read More At: What Is Artificial Intelligence?

Benefits of Natural Language Processing

Using natural language processing in business has a variety of benefits. For instance, NLP applications utilized in buyer assist roles may be lively 24/7 and can be cheaper to implement and maintain than a human employee. This makes NLP a potential cost-saving measure.

NLP may additionally be used to nurture leads and develop targeted promoting, guaranteeing that an organization’s products are being put in entrance of the eyes of the folks most probably to buy them. This might help increase the effectiveness of human advertising teams and drive revenue up without necessarily needing to spend money on more widespread advertising campaigns.

Natural language processing can be used to spice up seo (SEO) and help make sure a business stays as excessive in the rankings as attainable. NLP can analyze search queries, suggest associated keywords, and assist save time on SEO analysis, giving companies extra time to optimize their content high quality.

Top Natural Language Processing Companies


One of the biggest names in AI and tech, Google naturally has an extended historical past of using NLP in its services. Just this year, one of its researchers asserted that one of the company’s Language Model for Dialogue Applications (LamDA) was sentient, thanks largely to its responses to the researcher by way of text chat. Google even started public testing of LamDA in late August 2022.

In terms of product choices, it has a Natural Language API which allows customers to derive new insights from unstructured textual content. Its AutoML supplies custom machine learning models to higher analyze, categorize, and assess documents. The Dialogflow development suite could be deployed in quite lots of totally different settings to create conversational consumer interfaces similar to chatbots on web sites, cell apps, and other platforms.

Finally, Google Cloud’s Document AI resolution lets customers automate data capture at scale, permitting them to extract extra information from paperwork without boosting prices.

Read More At: The Future of Artificial Intelligence


Automated Insights’ Wordsmith platform is touted because the world’s first publicly-available pure language technology (NLG) engine. By inputting info into the engine, users can create clear, understandable content powered by AI.

Being one of many first of its sort, the platform has a number of fascinating shoppers. Notably, the Associated Press has partnered with Automated Insights to energy over 50,000 AI-generated news articles, according to Automated Insight’s website.

Wordsmith’s interface is certainly one of the best to use available on the market with a excessive degree of customizability. However, preliminary setup can take longer than anticipated. Those on the lookout for quick-deployment choices may must look elsewhere. The content material output may also probably need some touching up by in-house workers earlier than publication.

Overall, Wordsmith is a stable selection for firms on the lookout for a approach to convert large volumes of data into readable, formatted content material.

Indata Labs

Based out of Cyprus, Indata Labs leverages its employees’ experience in big information analytics, AI, and NLP to assist shopper corporations get probably the most out of their information. Organizations in industries like healthcare, e-commerce, fintech, and security have made use of Indata Labs’ experience to generate new insights from their information.

The firm offers a variety of providers and solutions, from information engineering to picture recognition to predictive analytics. In the NLP area, the firm presents buyer expertise consulting, shopper sentiment evaluation, and textual content analysis to make sure shoppers generate as much value from their datasets as potential.

Indata Labs additionally maintains its own in-house AI R&D (research and development) Center and works with a number of the finest laptop imaginative and prescient and NLP companies in the world to develop new solutions and push the fields of business intelligence, AI, and pure language processing ahead.


Another tech titan, IBM’s suite of Watson AI products are a variety of the best available on the market. Naturally, Watson’s big range of providers options a selection of NLP options. Watson Discovery is an clever search and text evaluation platform which enterprises can use to help discover information potentially hidden in their vast shops of information.

Watson Assistant is a buyer help platform which collects data from consumer conversations. Through this, Watson Assistant chatbots can higher discover methods to make the shopper support process less tense and time-consuming for patrons.

Finally, Watson Natural Language Understanding makes use of deep studying to determine linguistic ideas and keywords, perform sentiment analysis, and extract which means from unstructured knowledge.

Read More At: The Benefits of Artificial Intelligence


Synthesia is a web-based AI video era platform. Through its library of video templates, AI voices, and avatars, users can craft movies at-scale to meet whatever needs they may have. Synthesia’s tech has been used by over 10,000 firms, including Nike, Google, the BBC, and Reuters, to create videos in over 60 languages, according to its web site.

Other features on the platform embody a display screen recorder, custom AI avatar crafting, closed captioning, and access to a library of royalty-free background music. If a corporation has entry to its own library of media assets, they can simply upload after which use these property in Synthesia.


A main tech identify like Intel is certain to have a whole host of NLP-related services. There is, of course, Intel’s wide array of AI merchandise, from improvement instruments to deployment solutions.

For organizations interested in leveling up their NLP knowledge, Intel offers an extensive natural language processing developer course the place students can learn the ins and outs of truly using NLP in AI coaching.

There can be the Natural Language Processing Architect, a Python library developed by the Intel AI Labs. A Python library is, in essence, a set of premade collections of code which may be repeatedly implemented in different packages in scenarios. The NLP Architect specifically is supposed to help make creating custom NLP-trained AI simpler.


MindMeld provides a conversational AI platform through which companies can develop conversational interfaces designed to greatest go properly with their apps, algorithms, and platforms.

Through MindMeld, companies have developed and deployed interfaces for food ordering, house assistance, banking assistance, and video discovery. It provides training at each step of the NLP hierarchy, making certain each stage of logic within the process is accounted for.

It’s due to this progressive platform that Entrepreneur Magazine placed MindMeld in its 100 Brilliant Companies list in 2015. Companies utilizing MindMeld embrace Cisco, Appspace, Davra, and Altus.


Microsoft’s reach expands across the entire tech landscape. It’s no shock that AI, and by extension natural language processing, is one space of curiosity to the Washington-based tech giant. In fact, Microsoft’s Research Lab in Redmond, Washington, has a bunch dedicated specifically to NLP research.

Through Microsoft’s Azure cloud computing service, clients can train and deploy customized natural language processing frameworks. The company even provides documentation on how to do so. To utilize NLP in Azure, Microsoft recommends Apache Spark, an open-source unified analytics engine constructed for large-scale data processing.

Notable options of those custom-made NLP frameworks for Azure include sentiment analysis, textual content classification, text summarization, and embedding. Additionally, Microsoft’s Azure AI can support a multilingual training model, permitting organizations to train NLP AI to carry out in multiple completely different languages without retraining.

Read Next: What Is Deep Learning?

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