An AI service that uncovers insights such as sentiment, entities, and key phrases in unstructured text
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Extract insights from text
Discover insights in unstructured text using natural language processing (NLP)—no machine learning expertise required. Identify key phrases and entities such as people, places, and organizations to understand common topics and trends. Classify medical terminology using domain-specific, pretrained models. Gain a deeper understanding of customer opinions with sentiment analysis. Evaluate text in a wide range of languages.
Broad entity extraction
Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.
Powerful sentiment analysis
Examine what customers are saying about your brand, and detect sentiment around specific topics.
Robust language detection
Evaluate text input in a wide range of languages.
Run Text Analytics anywhere—in the cloud, on-premises, or at the edge in containers.
Identify and categorize important concepts
Classify a broad range of entities in text, such as people, places, organizations, date/time, and percentages, using named entity recognition. Detect and extract 100+ types of personally identifiable information (PII), including protected health information (PHI), in documents.
Extract key phrases in unstructured text
Quickly evaluate and identify the main points in unstructured text. Get a list of relevant phrases that best describe the subject of each record using key phrase extraction. Easily pull and organize information to make sense of important topics and trends.
Better understand customer perception
Detect positive and negative sentiment in social media, customer reviews, and other sources to get a pulse on your brand. Use opinion mining to explore customers’ perception of aspects, such as specific attributes of products or services, in text.
Process unstructured medical data
Extract insights from unstructured clinical documents such as doctors’ notes, electronic health records, and patient intake forms using the health feature of Text Analytics (gated public preview). Recognize, classify, and determine relationships between medical concepts such as diagnosis, symptoms, and dosage and frequency of medication.
Detect language of your text
Evaluate text input in a wide range of languages, variants, and dialects using the language detection feature.
Deploy anywhere, from the cloud to the edge
Run Text Analytics wherever your data resides. Build applications that are optimized for both robust cloud capabilities and edge locality using containers.
Comprehensive privacy and security
- Your data stays yours. Microsoft doesn’t use the training performed on your text to improve models.
- Choose where Cognitive Services processes your data with containers.
- Backed by Azure infrastructure, Text Analytics offers enterprise-grade security, availability, compliance, and manageability.
Get the power, control, and customization you need with flexible pricing
- Pay only for what you use, with no upfront costs.
- With Text Analytics, you pay as you go based on the number of transactions.
Trusted by companies of all sizes
KPMG streamlines fraud analytics
KPMG is helping financial institutions save millions in compliance costs with its Customer Risk Analytics solution, which detects specific text patterns and keywords to flag compliance risks.
Wilson Allen unlocks insights from unstructured data
Wilson Allen created a powerful AI solution that can help law and professional services firms around the world find unprecedented levels of insight in previously siloed and unstructured data.
IHC empowers service engineers
Royal IHC uses Azure Cognitive Search and Text Analytics to relieve its engineers from time-consuming manual data searches across disparate sources and give them insights on their structured and unstructured data.
LaLiga boosts fan engagement
LaLiga is engaging hundreds of millions of fans around the world with a personal digital assistant, using Text Analytics to process incoming queries and determine user intents in multiple languages.
TIBCO brings root cause analysis to the edge
TIBCO is using Text Analytics and Anomaly Detector to detect and analyze anomalies—sudden changes in data patterns, discover root causes, and provides suggested actions.
Kotak Mahindra Bank accelerates productivity
Kotak Asset Management is transforming customer service management by enabling chatbots to easily analyze subject line, customer information, and email content to identify sentiment and trigger the next best action.
Frequently asked questions about Text Analytics
Text Analytics detects a wide range of languages, variants, and dialects. See the language support documentation for more information.
No, the models are pretrained. Scoring, key phrase extraction, and language detection operations are available on uploaded data. To create and host custom models, explore the Language Understanding service.
Key phrase extraction eliminates non-essential words and standalone adjectives. Adjective-noun combinations, such as "spectacular views" or "foggy weather," are returned together. Generally, output consists of nouns and objects of the sentence and is listed in order of importance. Importance is measured by the number of times a particular concept is mentioned, or the relation of that element to other elements in the text.
Improvements to models and algorithms are announced if the change is major, and added to the service if the update is minor. Over time, you might find that the same text input results in a different sentiment score or key phrase output. This is a normal and intentional consequence of using managed machine learning resources in the cloud.