Natural Language AI
Derive insights from unstructured text using Google machine learning.
New customers get up to $300 in free credits to try Google Cloud products
Get insightful text analysis with machine learning that extracts, analyzes, and stores text
Train high-quality machine learning custom models without a single line of code with AutoML
Apply natural language understanding (NLU) to apps with Natural Language API
Benefits
Insights from customers
Insights from customers
Use entity analysis to find and label fields within a document—including emails, chat, and social media—and then sentiment analysis to understand customer opinions to find actionable product and UX insights.
Multimedia and multilingual support
Multimedia and multilingual support
Natural Language with Speech-to-Text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages.
Content targeting and discovery
Content targeting and discovery
Use Google's state-of-the-art language technology to classify content across media for better content recommendations and ad targeting.
Demo
Natural Language API demo
Try the API
Key features
Three natural language solutions that work with your text
AutoML
Train your own high-quality machine learning custom models to classify, extract, and detect sentiment with minimum effort and machine learning expertise using Vertex AI for natural language, powered by AutoML. You can use the AutoML UI to upload your training data and test your custom model without a single line of code.
Natural Language API
The powerful pre-trained models of the Natural Language API empowers developers to easily apply natural language understanding (NLU) to their applications with features including sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis.
Healthcare Natural Language AI
Gain real-time analysis of insights stored in unstructured medical text. Healthcare Natural Language API allows you to distill machine-readable medical insights from medical documents, while AutoML Entity Extraction for Healthcare makes it simple to build custom knowledge extraction models for healthcare and life sciences apps—no coding skills required.
By using custom entity extraction within AutoML Natural Language, we can use large data sets to train our model and continually improve the process, no matter where the document comes from.
Kiran Kaza, Head of Mobile Engineering, DocuSign
Documentation
Documentation
Cloud Natural Language API
Provide natural language understanding technologies, such as sentiment analysis, entity recognition, and other text annotations to developers.
Build custom ML models with AutoML for natural language data
Create models to classify documents, identify entities in documents, or analyze the prevailing emotional attitude in a document.
Cloud Natural Language API
In this lab, you'll learn how to create an API key Use the Cloud Natural Language API and extract "entities" (e.g. people, places, and events) from a snippet of text.
Not seeing what you’re looking for?
Which Natural Language product is right for you?
Natural Language API reveals the structure and meaning of text with thousands of pretrained classifications. AutoML classifies content in custom categories for your specific needs.
AutoML
Natural Language API
Integrated REST API
Natural Language is accessible via our REST API. Text can be uploaded in the request or integrated with Cloud Storage.
Integrated REST API
Natural Language is accessible via our REST API. Text can be uploaded in the request or integrated with Cloud Storage.
Syntax analysis
Extract tokens and sentences, identify parts of speech, and create dependency parse trees for each sentence.
Syntax analysis
Extract tokens and sentences, identify parts of speech, and create dependency parse trees for each sentence.
Entity analysis
Identify entities within documents—including receipts, invoices, and contracts—and label them by types such as date, person, and media.
Entity analysis
Identify entities within documents—including receipts, invoices, and contracts—and label them by types such as date, person, and media.
Custom entity extraction
Identify entities within documents and label them based on your own domain-specific keywords or phrases.
Custom entity extraction
Identify entities within documents and label them based on your own domain-specific keywords or phrases.
Sentiment analysis
Understand the overall opinion, feeling, or attitude sentiment expressed in a block of text.
Sentiment analysis
Understand the overall opinion, feeling, or attitude sentiment expressed in a block of text.
Custom sentiment analysis
Understand the overall opinion, feeling, or attitude expressed in a block of text tuned to your own domain-specific sentiment scores.
Custom sentiment analysis
Understand the overall opinion, feeling, or attitude expressed in a block of text tuned to your own domain-specific sentiment scores.
Content classification
Classify documents in 700+ predefined categories.
Content classification
Classify documents in 700+ predefined categories.
Custom content classification
Create labels to customize models for unique use cases, using your own training data.
Custom content classification
Create labels to customize models for unique use cases, using your own training data.
Multi-language
Analyze text in English, Spanish, Japanese, Chinese (simplified and traditional), French, German, Italian, Korean, Portuguese, and Russian.
Multi-language
Analyze text in English, Spanish, Japanese, Chinese (simplified and traditional), French, German, Italian, Korean, Portuguese, and Russian.
Custom models
Train custom machine learning models with minimum effort and machine learning expertise.
Custom models
Train custom machine learning models with minimum effort and machine learning expertise.
Powered by Google’s AutoML models
Leverages Google state-of-the-art AutoML technology to produce high-quality models.
Powered by Google’s AutoML models
Leverages Google state-of-the-art AutoML technology to produce high-quality models.
Spatial structure understanding
Use the structure and layout information in PDFs to improve custom entity extraction performance.
Spatial structure understanding
Use the structure and layout information in PDFs to improve custom entity extraction performance.
Large dataset support
Unlock complex use cases with support for 5,000 classification labels, 1 million documents, and 10 MB document size.
Large dataset support
Unlock complex use cases with support for 5,000 classification labels, 1 million documents, and 10 MB document size.
AutoML
Integrated REST API
Natural Language is accessible via our REST API. Text can be uploaded in the request or integrated with Cloud Storage.
Syntax analysis
Extract tokens and sentences, identify parts of speech, and create dependency parse trees for each sentence.
Entity analysis
Identify entities within documents—including receipts, invoices, and contracts—and label them by types such as date, person, and media.
Custom entity extraction
Identify entities within documents and label them based on your own domain-specific keywords or phrases.
Sentiment analysis
Understand the overall opinion, feeling, or attitude sentiment expressed in a block of text.
Custom sentiment analysis
Understand the overall opinion, feeling, or attitude expressed in a block of text tuned to your own domain-specific sentiment scores.
Content classification
Classify documents in 700+ predefined categories.
Custom content classification
Create labels to customize models for unique use cases, using your own training data.
Multi-language
Analyze text in English, Spanish, Japanese, Chinese (simplified and traditional), French, German, Italian, Korean, Portuguese, and Russian.
Custom models
Train custom machine learning models with minimum effort and machine learning expertise.
Powered by Google’s AutoML models
Leverages Google state-of-the-art AutoML technology to produce high-quality models.
Spatial structure understanding
Use the structure and layout information in PDFs to improve custom entity extraction performance.
Large dataset support
Unlock complex use cases with support for 5,000 classification labels, 1 million documents, and 10 MB document size.
Natural Language API
Integrated REST API
Natural Language is accessible via our REST API. Text can be uploaded in the request or integrated with Cloud Storage.
Syntax analysis
Extract tokens and sentences, identify parts of speech, and create dependency parse trees for each sentence.
Entity analysis
Identify entities within documents—including receipts, invoices, and contracts—and label them by types such as date, person, and media.
Custom entity extraction
Identify entities within documents and label them based on your own domain-specific keywords or phrases.
Sentiment analysis
Understand the overall opinion, feeling, or attitude sentiment expressed in a block of text.
Custom sentiment analysis
Understand the overall opinion, feeling, or attitude expressed in a block of text tuned to your own domain-specific sentiment scores.
Content classification
Classify documents in 700+ predefined categories.
Custom content classification
Create labels to customize models for unique use cases, using your own training data.
Multi-language
Analyze text in English, Spanish, Japanese, Chinese (simplified and traditional), French, German, Italian, Korean, Portuguese, and Russian.
Custom models
Train custom machine learning models with minimum effort and machine learning expertise.
Powered by Google’s AutoML models
Leverages Google state-of-the-art AutoML technology to produce high-quality models.
Spatial structure understanding
Use the structure and layout information in PDFs to improve custom entity extraction performance.
Large dataset support
Unlock complex use cases with support for 5,000 classification labels, 1 million documents, and 10 MB document size.
Take the next step
Start deriving insights from unstructured text using Google machine learning, with up to $300 in free credits.
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