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Top 5 NLP Platforms & Comparison in 2024

Cem Dilmegani
Updated on Jan 12
3 min read
Top 5 NLP Platforms & Comparison in 2024Top 5 NLP Platforms & Comparison in 2024

There are numerous API providers in the chatbot landscape, the majority of them are focusing on Natural Language Processing (NLP) and Natural Language Understanding (NLU). It is the crucial step to decide since it will be handling the most important step in a conversational interface.

What is the difference between NLP and NLU?

  • Natural Language Processing (NLP): In the artificial intelligence (AI) context, NLP is the overarching umbrella that encompasses several disciplines that tackle the interaction between computer systems and human natural languages. From that perspective, NLP includes several sub-disciplines such as discourse analysis, relationship extraction, natural language understanding and a few others language analysis areas (see Figure 2).
  • Natural Language Understanding (NLU): NLU is a subset of NLP that focuses on reading comprehension and semantic analysis. The combination of NLP and NLU technologies is becoming increasingly relevant on different software areas today including bot technologies. While there are many vendors and platforms focused on NLP-NLU technologies, the following technologies are becoming extremely popular within the bot developer community.

Figure 2: How NLP and NLU different.

Image shows jow NLU and NLP different.

To learn more about the differences between NLU and NLP you can read our NLU vs NLP: Main Differences & Use Cases Comparison article.

Top 5 NLP platforms

1. Dialogflow

Dialog Flow (ex has capabilities to build speech to text and text to speech, powered by machine learning. It provides built-support for currencies and date. Supports majority of the platforms like Facebook Messenger, Slack, Alexa, and Google Assistant. It supports multiple devices ranging from laptop computers to cars. Currently supports 20+ languages. It’s free for a limited number of queries.

2. is a free platform including for the commercial use. There are no limits on request number except they ask you to notify if you are going to exceed 1 request/sec. Supports many languages. On the other side, when your app is open, your intents, entities and validated expressions will be accessible to the community but not your logs, but still, you have the ownership of the data. Used by more than 120,000 developers. Supports not only chatbots but also wearables and home devices too.

3. Luis

Luis is Microsoft’s platform. It stands for Language Understanding (LUIS). A machine learning-based service to build natural language into apps, bots, and IoT devices. Quickly create enterprise-ready, custom models that continuously improve. It supports many services, but they have nice features for Azure integration.

4. Amazon Lex

Amazon Lex is an AWS service for building conversational interfaces into applications using voice and text. With Amazon Lex, the same deep learning engine that powers Amazon Alexa is now available to any developer, enabling you to build sophisticated, natural language chatbots into your new and existing applications. Amazon Lex provides the deep functionality and flexibility of natural language understanding (NLU) and automatic speech recognition (ASR) to enable you to build highly engaging user experiences with lifelike, conversational interactions and create new categories of products.

5. Watson Assistant

Watson Assistant, formerly Watson Conversation, helps you build an AI assistant for a variety of channels, including mobile devices, messaging platforms, and even robots. Create an application that understands natural-language and responds to customers in human-like conversation –in multiple languages. Seamlessly connect to messaging channels, web environments and social networks to make scaling easy. Easily configure a workspace and develop your application to suit your needs.

See our article about IBM Watson for more details.

Natural Language Platforms (NLP) Comparison

Below table is the comparison of these five NLP platforms based on their features.

Wit.aiDialogFlowLexLUISWatson Assistant
Training ModuleYesYesYesYesYes
Allow Import/Export ModelYesYesNoYesYes
Recognize User IntentYesYesYesYesYes
Pre-built EntriesBasic parametersMore than Basic ParametersHuge ListBasic ParametersBasic Parameters
Pre-built Intents (Domain of Knowledge)NoAround 35 DomainsNoAround 170 intentsNo
Save Progress through SessionYesYesYesYesYes
Speech RecognitionYesYes, through Google SpeechYesYes, through Bing SpeechYes, through IBM Speech to Text
Third-party IntegrationNoYesYesYesNo
Supported Languages1322051112
Limits for API callsUnlimitedUnlimitedTRIAL:
10k text queries
5k speech queries

FREE: 10k queries/month 5 queries/second PAID: 10 queries/second $0.75 per 1k queries
Free: 1k API queries/month PAID: Unlimited API queries/month Up to 20 work spaces Up to 2k intents Premium: Unlimited
TRIAL: 1 year PAID: $0.004 per speech query $0.00075 per text query
10k API queries/month

$0.75 per 1k querries
FREE: 1k API queries/month STANDARD: $0.0025 per API call PREMIUM: Available Upon Request
Good ForSimple B2C chatbots, MVPsMiddle Level B2C chatbots, virtual assistants, MVPsPreview Mode, too early to judgeCortana functionality, IoT applications, Virtual Assistants, and ChatbotsVirtual Assistants and chatbots that require IBM integration

Courtesy of (Digiteum)

If you still feel like you need NLP platform selection guide, feel free to check our related article.

To learn more regarding the future of NLP you can read our Top 5 Expectations Regarding the Future of NLP article.

And if you have a specific business challenge,

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Cem Dilmegani
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

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Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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Feb 15, 2021 at 13:01

Thanks for this comparison!
In case you are interested, please not that we recently released a new NLP API called NLP Cloud (
It basically does named entity recognition and part of speech tagging. It is using the spaCy Python library under the hood so you can either use pre-trained models and it just works out of the box, or upload your own custom models trained with spaCy.
All the small spaCy models are free.

Matheus Enrique Alves
Oct 14, 2019 at 12:43

Great Guide!
Have you heard about ?

It’s a new option for NLU!

Roman Chuprina
Oct 01, 2019 at 10:49

That’s a great guide, thank you for your work. I think Natural Language Processing has a big potential as a part as Artificial Intelligence technology. Chatbots are great for many industries, with the most beneficial being Retail. I recently wrote an article on NLP, and I am very optimistic about future of this technology. Everything necessary for this technology is here, the question is in how good it can be. Considering the current state, we will see some major improvement very soon.

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