Merge pull request #4890 from laujan/kate-4466-pro-standard-modes-only

standard and pro modes

Author: Stacyrch140

articles/ai-services/content-understanding/concepts/standard-pro-modes.md

@@ -0,0 +1,95 @@
+---
+title: Azure AI Content Understanding standard and pro modes
+titleSuffix: Azure AI services
+description: Learn about Azure AI Content Understanding standard and pro modes.
+author: laujan
+ms.author: kabrow
+manager: nitinme
+ms.service: azure-ai-content-understanding
+ms.topic: overview
+ms.date: 05/19/2025
+---
+
+# Azure AI Content Understanding pro and standard modes
+
+Azure AI Content Understanding is an advanced generative AI service designed to derive structured insights from multi-modal content such as documents, images, videos, and audio. With the introduction of the `2025-05-01-preview` version, the service now offers two distinct modes: `standard` and `pro`.
+
+* **Standard**: This mode serves as the default solution for processing diverse content types. It's optimized to provide efficient schema extraction tailored to specific tasks across all data formats. This mode emphasizes cost-effectiveness and reduced latency, ensuring structured insights are accessible for your general processing needs.
+
+* **Pro**: This mode is designed for advanced use cases, particularly those requiring multi-step reasoning, and complex decision-making. It supports complex tasks such as identifying inconsistencies, drawing inferences, and making sophisticated decisions. The pro mode allows input from multiple content files and includes the option to reference external data for enriched and validated results. Currently, pro mode is only offered for your document-based data.
+
+## Standard mode overview
+
+The Content Understanding standard mode delivers structured insights across various data types, including documents, videos, images, audio, and text. While it doesn't support data inferencing, it minimizes cost and latency, making it ideal for broad, data-centric scenarios. This mode enables the creation or customization of schemas to extract precise insights tailored to your needs. Additionally, it incorporates data labeling for document data, allowing human input to enhance the quality of your outputs.
+
+### Standard mode: use case
+
+Standard is the ideal service for extracting the exact insights you need on any type of data. If you're just looking to unlock the content of your data, your scenario may not require complex reasoning or decision making. Scenarios that standard mode works great for include:
+
+* Structuring data to power your RAG search workflows and integrating with [AI Search](../../../search/search-what-is-azure-search.md).
+* Extracting data to integrate with [Microsoft Fabric](https://blog.fabric.microsoft.com/en-US/blog/).
+* Analyzing advertising videos to screen for content guidelines.
+* Segmenting video footage to create chapters and identify ideal advertising breaks.
+* Extracting critical data points from sports games and providing post-game recaps.
+
+## Pro mode overview
+
+Content Understanding pro mode  is tailored for customers with highly complex use cases, offering advanced multi-step reasoning capabilities. It enables reasoning over both input content and reference data provided by customers, making it ideal for scenarios requiring deep comprehension and complex decision-making. By incorporating reference data, pro mode  adds context to each request, aiding tasks such as validation and enrichment, which reduces the need for human intervention and boosts productivity. For multiple input documents, it supports integration of reference datasets enriching workflows with external data for linking, validation, and enrichment. Currently, pro mode  is exclusively available for document data.
+
+
+### Pro mode reference data
+
+When your goal is to extract specific data points from your documents, reference data defines these data points and provides the service context it needs to validate whether the data passes the required criteria. For example, if you're looking to analyze invoices to ensure they're consistent with a contractual agreement, the signed contract serves as the reference data, allowing the service to compare the data in the contract to the individual invoices. In doing this comparison, the service applies reasoning to validate that either the invoices are in accordance with the contract or identify discrepancies and flag for further review.
+
+### Multi-step reasoning
+
+Multi-step reasoning offers the ability to decompose complex problems into a simples tasks. Multi-step reasoning takes data analysis a step further than extracting and aggregating structured data and allows you to draw conclusions on that data, minimizing the need for human review. Examples of the types of questions pro mode can answer with multi-step reasoning include:
+
+* Does x match y?
+* Does x pass the outlined criteria?
+* Does x scenario follow the required guidelines?
+* Does the total equal the sum of the items?
+* Find all inconsistencies between the invoice and the contract.
+
+## Standard and pro mode features
+
+Not sure which mode is right for your scenario? The following charts compare standard and pro mode features.
+
+| Feature | Standard mode | Pro mode |
+|----|----|----|
+| **Large documents** | Yes  | Yes |
+| **Field mode** | Yes | Yes |
+| **Ability to extract, classify, and generate fields** | Yes | Yes |
+| **Grounding and confidence scores** | Yes | No |
+| **Input document type** | Documents, images, video, audio | Documents |
+| **Max fields** | 100 | 100 |
+| **Multiple input document processing** | No | Yes |
+| **Reference dataset integration** | No  | Yes |
+| **Multistep reasoning** | No  | Yes |
+
+
+## Apply standard or pro mode to your scenarios
+
+ You can apply both Content Understanding standard and pro modes to just about any scenario, but how you build your solution depends on the questions you're aiming to answer. The following scenarios present examples of how you might apply standard and pro modes to your data.
+
+| Scenario | Standard mode | Pro mode|
+|----|----|----|
+| **Invoice analysis** | Extract insights on invoice data at scale and enable RAG search and further data analysis and visualization. Answer questions like: <br> &bullet; Extract purchase order number, total, due date, and line items for entry into database. | Analyze invoices and contractual agreements with clients and apply multi-step reasoning to draw conclusions on that data. Answer questions like: <br> &bullet; Does this invoice fulfill the contractual agreement we have in place with this client? <br> &bullet; Does this invoice need further review |
+| **Call center transcript analytics** | Extract insights on large volumes of call center data to gain valuable insights on sentiment, understand customer issues, and create targeted training to address major pain points. Answer questions like: <br> &bullet; What are the main issues customers are calling about? <br> &bullet; What is the average length of calls made about x issue? | Analyze call center transcript data and apply multi-step reasoning to understand how call center employees are addressing customer needs, and if they're following guidelines. Answer questions like: <br> &bullet; Did the call center employee introduce themselves? <br> &bullet; Did this answer "pass" certain criteria? |
+| **Mortgage application processing** | Extract the key values from mortgage application data and make it searchable and more easily accessible. Answer questions like: <br> &bullet;  What year was the mortgage application submitted? <br> &bullet; What are the names on the application? | Analyze supplementary supporting documentation and mortgage applications to determine whether a prospective home buyer provides all the necessary documentation to secure a mortgage. Answer questions like: <br> &bullet;  Do the names and social security numbers on the mortgage application match the supporting documentation? |
+
+## Try pro mode
+
+You can try out the features of both Content Understanding standard and pro modes using the [Azure AI Foundry](https://ai.azure.com/explore/aiservices/vision/contentunderstanding). The service enables you to bring your own data and experiment with all the functionalities of both modes in a lightweight, no-code approach to help you find the best fit for your unique scenario.
+
+### Pro mode known limitations
+
+* Content Understanding pro mode currently doesn't offer confidence scores or grounding. It currently supports generative and classification of your fields but doesn't support extraction only.
+* Content Understanding pro mode is currently only available for documents.
+
+## Next steps
+
+For more information on document processing, see [Document processing overview](../document/overview.md).
+
+
+

articles/ai-services/content-understanding/toc.yml

@@ -76,6 +76,9 @@ items:
     - name: Accuracy and confidence
       displayName: accuracy, confidence, analyzers, optimization, fields, scores
       href: concepts/accuracy-confidence.md
+    - name: "🆕 Modes: standard and pro"
+      displayName: standard, pro, modes, analyzers, optimization, fields
+      href: concepts/standard-pro-modes.md
     - name: 🆕 Classifier
       displayName: classifier, text, images, video, audio, multimodal, visual, structured, content, field, extraction
       href: concepts/classifier.md