Azure AI Content Understanding

Introduction

Azure AI Content Understanding empowers you to transform unstructured multimodal data—such as text, images, audio, and video—into structured, actionable insights. By streamlining content processing with advanced AI techniques like schema extraction and grounding, it delivers accurate structured data for downstream applications. Offering prebuilt templates for common use cases and customizable models, it helps you unify diverse data types into a single, efficient pipeline, optimizing workflows and accelerating time to value.

Core Features

• Multimodal data ingestion
  Ingest a range of modalities such as documents, images, audio, or video. Use a variety of AI models to convert the input data into a structured format that can be easily processed and analyzed by downstream services or applications.
• Customizable output schemas
  Customize the schemas of extracted results to meet your specific needs. Tailor the format and structure of summaries, insights, or features to include only the most relevant details—such as key points or timestamps—from video or audio files.
• Confidence scores
  Leverage confidence scores to minimize human intervention and continuously improve accuracy through user feedback.
• Output ready for downstream applications
  Automate business processes by building enterprise AI apps or agentic workflows. Use outputs that downstream applications can consume for reasoning with retrieval-augmented generation (RAG).
• Grounding
  Ensure the information extracted, inferred, or abstracted is represented in the underlying content.
• Automatic labeling
  Save time and effort on manual annotation and create models quicker by using large language models (LLMs) to extract fields from various document types.

Use Cases

• Post-call analytics for call centers: Generate insights from call recordings, track key performance indicators (KPIs), and answer customer questions more accurately and efficiently.
• Tax process automation: Streamline the tax return process by extracting data from tax forms to create a consolidated view of information across various documents.
• Media asset management: Extract features from images and videos to provide richer tools for targeted content and enhance media asset management solutions.
• Chart understanding: Enhance chart understanding by automating the analysis and interpretation of various types of charts and diagrams using Content Understanding.

Benefits

• Streamline workflows: Azure AI Content Understanding standardizes the extraction of content, structure, and insights from various content types into a unified process.
• Simplify field extraction: Field extraction in Content Understanding makes it easier to generate structured output from unstructured content. Define a schema to extract, classify, or generate field values with no complex prompt engineering.
• Enhance accuracy: Content Understanding employs multiple AI models to analyze and cross-validate information simultaneously, resulting in more accurate and reliable results.
• Confidence scores & grounding: Content Understanding ensures the accuracy of extracted values while minimizing the cost of human review.

Technical Details

• Deployment: Deployment options may vary by service, reference the following docs for more information: Create an Azure AI Services multi-service resource .
• Requirements: Requirements may vary depending on the input data you are analyzing, reference the following docs for more information: Service quotas and limits .
• Support: Support options for AI Services can be found here: Azure AI services support and help options .

Pricing

View up-to-date pay-as-you-go pricing details here: Azure AI Content Understanding pricing .