In this blog you’ll discover how Microsoft Syntex transforms how businesses manage their incoming and outgoing data and documents by automating repeatable, document-based processes. From invoices and contracts to statements of works, service agreements and letters of consent, it makes the otherwise detailed and laborious tasks of finding, organising and creating essential, standard documents a breeze.

Firstly, we’ll explain what Microsoft Syntex content AI is and what you can do with it. We’ll then explore content-related services in Microsoft Syntex, focussing on document processing and content assembly. Together these two services can automate document processes efficiently while ruling out the margin for human error. Finally we’ll look at example use cases to highlight these services in action. Ideal for businesses that have defined repeatable processes for their documentation, producing documents such as contracts and invoices has never been easier.

If you’d like to discuss how your business can harness the power of Microsoft Syntex, contact us for a free discussion with one of our certified technical consultants.

What is Microsoft Syntex?

At its core, Microsoft Syntex is based on machine learning models that ingest and analyse the files you have stored in Office 365, including SharePoint, Teams, OneDrive and Exchange to extract the information you need.

It’s a powerful content understanding, processing, and compliance service that uses intelligent document processing, content artificial intelligence (AI) and advanced machine learning to find, organise and classify documents in your SharePoint libraries. It intelligently automates content-based processes including:

  • Document processing (data extraction and classification)
  • Providing pre-built models for contracts, invoices and receipts
  • Training structured models for your documents e.g. forms
  • Training unstructured models for your documents e.g. letters
  • Content assembly (which is like mail merge for SharePoint)
  • Document translation
  • Optical character recognition
  • Merging and extracting data from PDFs of contracts, invoices and receipts
  • SharePoint eSignature involving process flow for signing for documents
  • Image tagging

In terms of use cases, Microsoft Syntex is ideal for automating processes that are labour-intensive, repetitive, and require accuracy. This can include processing incoming documents like supplier invoices, insurance forms, and rental contracts, as well as creating outbound documents such as letters and contracts – let’s find out how.

Document processing – extracting the data you need

Document processing involves both data extraction and classification. You may have a large volume of incoming documents, such as invoices, receipts or contracts from which you need to extract specific data. Microsoft Syntex offers pre-built plug and play models to allow you to extract the data that you want from documents.

The tool provides models for structured documents such as forms, which can be trained to consistently extract data from your specific document types. Similarly, for unstructured documents like proposals, letters, or contracts with varying data locations, different types of models can be trained to meet those specific requirements. Ultimately, the aim is to automate the extraction of data from documents and use that data effectively for your business.

Data extraction from structured documents

Let’s look at data extraction from structured documents, specifically invoices. Invoices typically follow a standardised template, with the consistent placement of key information such as invoice date, invoice number, VAT number, company name and total amount. Extracting accurate data from PDF documents can be challenging and often requires expensive third-party solutions. Microsoft Syntex simplifies this entire process. 

The document extraction process can be initiated automatically as soon as the document is uploaded to the library or you can manually trigger the extraction process by selecting the document you wish to process. 

Behind the scenes, you’re easily able to create a model to perform the necessary computations before training it to identify the data you need. You only need around five to ten samples to feed into the model you’ve created. The model can then extract the data and present it to you to review. If any errors are identified, the model will automatically refine itself. Once this process is complete, you can apply the trained model to your document library. 

There are further opportunities to make use of the data you’ve extracted using Power Automate workflows, such as sending this data to a database or CRM system or emailing users, for example to notify them that a document has been uploaded or that action needs to be taken. 

Data extraction from semi-structured documents

For the example of a semi-structured document, let’s use the example of a fictional airline management organisation. 

The organisation regularly receives incident reports written by one of its captains or another pilot and these documents may have areas with tables and other structured data. Other sections may be unstructured as the narrative is individual to the specific flight and scenario.  

In this instance, you can train your model to identify areas in each report from which it can extract specific data, for example, incident date, flight number, airline name, and airline manufacturer name.

You can also define closeness to words and use those rules to train your model before deploying it to your SharePoint library. 

Content assembly – using data from different sources

Content assembly in Microsoft Syntex involves using automation to populate fields in template documents that you create with data from different sources or data that has been extracted during the document processing step – think of it like Mail Merge for SharePoint. Models can be configured and trained through the Microsoft 365 Admin Center, while users interact with document libraries in SharePoint as usual. 

Taking the example of invoicing again, you may have a standard template that you use to send invoices to an invoice factoring company to chase outstanding invoices. You may give the company multiple invoice documents with placeholders for fields such as bank name, customer name, address and company number etc. Key data will need to be extracted from your original invoices, while individual customer details such as name, contact details and email address may be found in another location such as a list on SharePoint. Using Microsoft Syntex’s content assembly feature, you can easily carry out the otherwise onerous task of combining data from both sources and inserting it into your template document that you then send off to the invoice factoring company. 

Microsoft Syntex pricing

Microsoft Syntex operates a pay-as-you-go model, where each transaction incurs a small charge billed against your subscription. To set up, the tool needs to be linked to your Azure subscription.

Summary

To summarise, Microsoft Syntex is a powerful tool that uses document processing and content assembly capabilities to provide a seamless, end-to-end solution for managing your documents and your business data.

With the assistance of artificial intelligence, Microsoft Syntex is able to analyse and understand the content within documents, extracting valuable information and organising it in a structured way. This enables users to search, classify, and manage their documents, more efficiently than ever before. Additionally, Microsoft Syntex’s content assembly feature allows for the creation of dynamic templates, automating the process of generating personalised documents. 

It offers a comprehensive solution for document management, empowering organisations to streamline their workflows and enhance collaboration.

What Next?

If you have a potential use case that you’d like to discuss, please contact us for a free discussion with one of our certified technical consultants. We’re a trusted Microsoft Solutions Partner for Data & AI and we’ll be happy to help.

Published On: February 23rd, 2024 / Categories: Azure / Tags: , /

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