Optimize Unstructured Document Processing with Microsoft Syntex

Use the unstructured document processing model (teaching method) to automatically classify files and extract information. It works best for unstructured documents, such as letters or contracts.

The unstructured document processing model (formerly known as document understanding model) uses artificial intelligence (AI) to process documents. These documents must have text that can be identified based on phrases or patterns. The identified text designates both the type of file it is (its classification) and what you’d like to extract (its extractors).

Overview of unstructured document processing in Microsoft Syntex - Microsoft Syntex | Microsoft Learn

Overview of Microsoft Syntex - Microsoft Syntex | Microsoft Learn

Overview of Microsoft Syntex - Microsoft Syntex | Microsoft Learn

What is Microsoft Syntex?

Microsoft Syntex is an AI-powered content understanding and processing solution built on the Microsoft 365 platform. It uses machine learning and natural language processing (NLP) to help organizations automate the extraction of information from their unstructured content, such as documents, images, and audio files.

Syntex is designed to help organizations capture, categorize, and reuse knowledge from their content, making it easier to find, manage, and leverage. The solution can automatically apply metadata to content, making it easier to classify, search, and reuse. Syntex also uses AI models to identify and extract key information from content, such as people, organizations, and locations, and it can also analyze content to detect patterns and anomalies.

Syntex includes several pre-built models, such as the Invoice Processing model, which can automatically extract key data from invoices, and the Contract Analysis model, which can identify key clauses and terms in contracts. Organizations can also build and train their own models using the Microsoft Power Platform.

Overall, Microsoft Syntex provides organizations with a powerful tool for unlocking insights and knowledge from their content, improving productivity, and reducing costs associated with manual content processing.