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Natural Language AI

Derive insights from unstructured text using Google machine learning.

Industry leading accuracy

Insightful text analysis

Natural Language uses machine learning to reveal the structure and meaning of text. You can extract information about people, places, and events, and better understand social media sentiment and customer conversations. Natural Language AI enables you to analyze text and also integrate it with your document storage on Cloud Storage.


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. Learn more.

Natural Language API demo

How AutoML works

How AutoML Natural Language works1. Upload your documents. Label text based on your domain- specific keywords and phrases. 2. Train your custom model. Classify, extract, and detect sentiment. 3. Evaluate. Get insights that are relevant to your specific needs.Label text based on your domain- specific keywords and phrasesClassify, extract, and detect sentimentGet insights that are relevant to your specific needs3. Evaluate2. Train your custom model1. Upload your documents+1.0-1.0Orders Receipts InvoicesNotes Info Requests ComplaintsTXT


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 Multilingual Support

Multimedia and multilingual support

Combine Natural Language with our Speech-to-Text API to extract insights from audio conversations. Use it with optical character recognition (OCR) in our Vision API to understand scanned documents. Extract entities and understand sentiments in multiple languages.

Extract Key Document

Extract key document entities that matter

Use custom entity extraction to identify domain-specific entities within documents — many of which don’t appear in standard language models — without having to spend time or money on manual analysis.

Receipt and Invoice

Receipt and invoice understanding

Entity extraction can identify common entries in receipts and invoices — dates, phone numbers, companies, prices, and so on — to help you understand the relationships between a request and proof of payment. It even validates addresses with Google Maps.

Content Classification

Content classification relationship graphs

Classify documents by common entities, domain-specific customized entities, or 700+ general categories, like sports and entertainment. Syntax analysis can help you build relationship graphs of the entities extracted from news or Wikipedia articles.

Google Deep Learning

Best of Google deep-learning models

The Natural Language API offers you the same deep machine learning technology that powers both Google Search’s ability to answer specific user questions and the language-understanding system behind Google Assistant.

Which Natural Language product is right for you?

You can work with either one or reap the benefits of both products by using Natural Language API to quickly reveal the structure and meaning of text — using thousands of pretrained classifications — and using AutoML to classify content into custom categories to suit 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.

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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, contact information, organization, location, events, products, 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.



Enables you to easily analyze text in multiple languages including English, Spanish, Japanese, Chinese (simplified and traditional), French, German, Italian, Korean, Portuguese, and Russian.

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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.


Our Customers


Natural Language products Pricing guide
Natural Language API Pricing
AutoML Pricing


Google Cloud

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Create a custom machine learning model to classify content into domain-specific categories.

Natural Language API

Create a pre-trained machine learning model to reveal the structure and meaning of text.

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