Best Natural Language Processing (NLP) APIs in 2025

In the realm of Natural Language Processing (NLP), APIs play a crucial role in enabling developers to integrate sophisticated language capabilities into their applications. This blog post will explore the top 10 APIs in the category of NLP, providing a detailed overview of each API, its endpoints, and practical use cases. From sentiment analysis to language detection, these APIs offer powerful tools for developers looking to enhance their applications with language understanding and processing capabilities.

1. Multilingual Sentiment Analysis API

The Multilingual Sentiment Analysis API is an AI-based tool that detects the sentiment expressed in a given text. It analyzes the text to determine whether the sentiment is positive, neutral, or negative, supporting over 50 languages including Chinese, Italian, Japanese, Hindi, English, Spanish, and Russian.

Endpoints

Analyzer

The Analyzer endpoint allows users to pass a text for sentiment analysis. It returns a sentiment score and its label, which can be positive, negative, or neutral. The endpoint supports multiple languages, making it versatile for global applications.

{
  "results": [
    {
      "text": "This sentiment analyzer is amazing. It covers many more languages than I have used so far.",
      "label": "positive",
      "confidence": "0.99"
    }
  ]
}

In this response, the text field contains the analyzed input, the label indicates the sentiment classification, and the confidence provides a score between 0 and 1 representing the certainty of the prediction.

Common Use Cases

• Product Design and Improvement: Companies can analyze customer feedback on products to identify areas for improvement.
• Support Center Sentiment Analysis: Monitor customer interactions in real-time to gauge satisfaction levels.
• Measuring Customer Satisfaction: Analyze online reviews to understand customer sentiment towards a brand.

2. Part-Of-Speech Tagging API

The Part-Of-Speech Tagging API helps tag different parts of speech in any provided text, identifying nouns, verbs, adjectives, adverbs, and more.

Endpoints

POS Tagging

The POS Tagging endpoint tags the provided text with parts of speech. It returns a JSON object containing tagged parts of speech for each token in the text.

{
  "badRequest": false,
  "creditsUsed": 1,
  "errors": [],
  "sentences": [
    {
      "tokens": [
        {
          "labels": [{"label": "EX", "score": 0.9999990463256836}],
          "text": "There"
        },
        {
          "labels": [{"label": "VBZ", "score": 0.9999969005584717}],
          "text": "is"
        }
      ]
    }
  ]
}

In this response, the tokens array contains individual words with their respective labels indicating the part of speech and a score representing the confidence level of the tagging.

Common Use Cases

• Semantic Information Retrieval: Extract meaningful information from texts for analysis.
• Machine Learning Training: Use tagged data to train models for recognizing parts of speech.

3. Language Detection API

The Language Detection API allows developers to detect the language of a given text input using advanced NLP techniques.

Endpoints

Detector

The Detector endpoint analyzes the input text and returns the detected language along with a confidence score.

{
  "language_list": [
    {
      "iso639-2": "en",
      "language": "en",
      "name": "English",
      "relevance": 100
    }
  ],
  "status": {
    "code": "0",
    "msg": "OK",
    "credits": "1",
    "remaining_credits": "699644"
  }
}

The language_list array contains detected languages with their ISO codes and relevance scores, while the status field provides information about the request's success.

Common Use Cases

• Machine Translation: Automatically detect the source language for accurate translations.
• Text-to-Speech Systems: Use detected language to select appropriate voice and pronunciation.

4. Language Recognizer API

The Language Recognizer API is designed for quickly identifying the language of text, supporting 164 languages and batch requests.

Endpoints

LanguageLearning

The LanguageLearning endpoint detects languages of multiple texts at once, returning results for each text input.

{
  "data": {
    "detections": [
      [{"language": "es", "isReliable": true, "confidence": 10.24}],
      [{"language": "en", "isReliable": true, "confidence": 13.65}]
    ]
  }
}

The detections array contains results for each text, including the detected language, reliability, and confidence score.

Common Use Cases

• Content Management Systems: Automatically detect language for user-generated content.
• Customer Service: Route inquiries to agents based on detected language.

5. Named Entity Extractor API

The Named Entity Extractor API enables developers to extract named entities such as people, organizations, and locations from text.

Endpoints

Entity Extractor

The Entity Extractor endpoint extracts entities from the provided text and categorizes them.

{
  "result": {
    "PERSON": ["Elon Musk"],
    "ORG": ["SpaceX", "Tesla Motors"],
    "DATE": ["1999", "2002"],
    "NORP": ["American"]
  },
  "model_used": "lingo(en)",
  "time": "19.0ms"
}

The result object contains categorized entities, allowing developers to easily integrate this data into applications.

Common Use Cases

• Information Retrieval: Extract entities for use in search and retrieval systems.
• Chatbots: Enhance responses by recognizing entities in user inputs.

6. Text Tagging API

The Text Tagging API provides part-of-speech tagging, phrase chunking, and named entity recognition.

Endpoints

Text Tagging

The Text Tagging endpoint analyzes text to identify parts of speech, phrases, and named entities.

{
  "text": "The quick brown fox jumps over the lazy dog.",
  "tags": [
    {"word": "The", "tag": "DT"},
    {"word": "quick", "tag": "JJ"},
    {"word": "brown", "tag": "JJ"},
    {"word": "fox", "tag": "NN"}
  ]
}

The tags array contains each word with its corresponding part-of-speech tag, facilitating further analysis.

Common Use Cases

• Sentiment Analysis: Identify sentiment in customer reviews by analyzing parts of speech.
• Search Engines: Improve search accuracy by understanding user queries.

7. Text Emotion Recognition API

The Text Emotion Recognition API identifies and interprets emotions expressed in text.

Endpoints

Recognition

The Recognition endpoint analyzes text to identify emotions and overall sentiment.

{
  "confidence_score": 0.999,
  "emotions": {
    "happiness": 0.85,
    "sadness": 0.05
  },
  "overall_sentiment": "Positive",
  "summary": "The overall sentiment is positive with a high confidence score."
}

The emotions object lists detected emotional states, while the overall_sentiment provides a general classification.

Common Use Cases

• Social Media Monitoring: Analyze sentiment towards brands in real-time.
• Customer Service Management: Detect customer emotions to route queries effectively.

8. AI Text Detector API

The AI Text Detector API analyzes text to determine if it was generated by AI or a human.

Endpoints

Get Probability

The Get Probability endpoint analyzes text and returns the likelihood of it being AI-generated or human-written.

{
  "confidence": "high",
  "predicted_class": "human",
  "probabilities": {
    "ai": 0.1,
    "human": 0.9
  }
}

The predicted_class indicates the classification, while the probabilities object provides numerical values for each classification.

Common Use Cases

• Content Moderation: Identify AI-generated content to prevent misinformation.
• Fraud Detection: Flag messages generated by AI chatbots in customer interactions.

9. Google Language Translation API

The Google Language Translation API facilitates real-time translation across multiple languages.

Endpoints

Detect Language

The Detect Language endpoint identifies the language of a given text.

{
  "detectedLanguageCode": "fr"
}

The detectedLanguageCode provides the ISO code of the detected language.

Translate

The Translate endpoint translates text from one language to another.

{
  "translation": "Bonjour"
}

The translation field contains the translated text, allowing for seamless communication across languages.

Common Use Cases

• Multilingual Content Websites: Provide dynamic translations for global audiences.
• Global Customer Support: Translate customer queries in real-time for effective communication.

10. Multilingual Text Detection API

The Multilingual Text Detection API accurately identifies the language of text, ensuring effective communication in a globalized world.

Endpoints

Detection

The Detection endpoint analyzes text to identify its language.

{
  "iso": "de",
  "language": "German"
}

The iso field provides the ISO code, while the language field specifies the detected language.

Common Use Cases

• Content Localization: Tailor user experiences based on detected language.
• Translation Services Optimization: Streamline workflows by identifying source languages.

Conclusion

In conclusion, the APIs discussed in this blog post represent some of the most powerful tools available for developers working in the field of Natural Language Processing. From sentiment analysis to language detection, these APIs provide essential capabilities that can enhance applications across various domains. By leveraging these APIs, developers can create more intelligent, responsive, and user-friendly applications that cater to a global audience. Whether you are building a chatbot, a translation service, or a content management system, integrating these APIs can significantly improve the functionality and user experience of your applications.