Audience

Companies in search of a solution to accelerate their multimodal AI app development operations

About Azure AI Content Understanding

Azure AI Content Understanding helps enterprises transform unstructured multimodal data into insights. Derive meaningful insights from diverse types of input data, ranging from text, audio, images, and video. Achieve precise, high-quality data for downstream applications with sophisticated AI methods such as scheme extraction and grounding. Streamline and unify pipelines of varied data types into a single streamlined workflow, reducing overall costs and accelerating time to value. See how businesses and call center operators generate valuable insights from call recordings to track essential KPIs, enhance product experiences, and respond to customer inquiries more swiftly and accurately. Ingest a range of modalities, such as documents, images, audio, or video, and use a range of AI models available in Azure AI to transform input data into structured output that can be easily processed and analyzed by downstream applications.

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Integrations

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Company Information

Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/products/ai-services/ai-content-understanding

Videos and Screen Captures

Azure AI Content Understanding Screenshot 1
Azure AI Content Understanding Screenshot 1 Azure AI Content Understanding Screenshot 2
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Product Details

Platforms Supported
Cloud
Training
Documentation
Webinars
In Person
Videos
Support
Phone Support
24/7 Live Support
Online

Azure AI Content Understanding Frequently Asked Questions

Q: What kinds of users and organization types does Azure AI Content Understanding work with?
Q: What languages does Azure AI Content Understanding support in their product?
Q: What kind of support options does Azure AI Content Understanding offer?
Q: What other applications or services does Azure AI Content Understanding integrate with?
Q: What type of training does Azure AI Content Understanding provide?

Azure AI Content Understanding Product Features

Natural Language Processing

Sentence Segmentation
Tokenization
Stemming/Lemmatization
Part-of-Speech Tagging
Parsing
Named Entity Recognition
Co-Reference Resolution
In-Database Text Analytics
Open Source Integrations
Natural Language Generation (NLG)