SharePoint Syntex (formally part of Project Cortex) was released publicly at Microsoft Ignite 2020. Syntex is Microsoft’s first serious foray at infusing artificial intelligence functionality into SharePoint, the document management system many of us has come to use and (sort of) love in the corporate world over the last 15 years. It’s a critical tool for both managing documents and collaborating on content among teams. So with all the changes Microsoft has introduced into SharePoint in the last few years, the AI component was discernibly inevitable. And it’s a cool little tool – if you have the right use cases for it.
This blog post is dedicated to giving you the down-and-dirty intro to Syntex, including what it is, applicable scenarios, and why even bother with it. There’s already a lot written about how to configure and set it up (not the least of which is provided by Microsoft), so let’s focus on what matters from a business (and analyst) perspective.
In testing Syntex, I found that there were many good things that created genuine improvements on the SharePoint experience. After the initial configurations and learning the document processing model creation cycle, I can genuinely see how this might benefit organizations in the future – especially if said organizations are open to business change.
Rather than input document library metadata manually, Syntex basically allows users to upload documents and walk away. The model will fill in the library columns on its own. This saves time and effort.
The model design works with SharePoint to basically create new content types and site columns. All are available within the Content Type Gallery in the Admin Center. You can even let Syntex work with your Term Store to auto-tag documents based on your taxonomy. You can even auto-apply retention labels to the different content types as they come in.
By tying Syntex models to document libraries, content and metadata is automatically indexed across your tenant to be searchable and usable. This means teams and business units can more easily find what they need.
In my configuration and trial adventures of Syntex, it didn’t go all peaches ‘n cream. As with my usual experience with Microsoft 365, the vendor tends to over-market their products as simple, intuitive and far-reaching in terms of improving the digital workplace experience. There were a few things that left me wanting in terms of a better user experience, as well as a better consumer of this new product.
As discussed, you could provide documents of many types and build highly trained, complex processing models with very accurate classifiers and extractors. But accuracy results will differ based on a number of factors. This is even more true on a customer-to-customer basis. Consumers need to be aware that what works for a colleague or a partner organization may not work as effectively for another. It’s all about sandboxing, sandboxing, and more sandboxing.
Microsoft brands Syntex as low-code, easy to learn, and quick to jump in. I beg to differ, even as an analyst with a technical background. It will take practice and a deep understanding of both the model learning process, the user interface, and information architecture in general. For modeling to be successful, digital workplace teams will need to dedicate resources internally to learn, build, and curate processing models so that users can generate value out of Syntex and its capabilities.
The Syntex advertisements and marketing material has warts – or at least the way it’s contextualized. Signing up for a Syntex license only provides the Document Understanding processing model, not the Forms Processing Model – although you may be lead to believe it’s all one and the same. These are two different technologies with different investment costs. Read the fine print, do your research, and make sure you know what you’re getting with a Syntex license (and what you’re not).
As with any piece of software or functionality, there are limitations with Syntex – and when I say “Syntex”, I mean the Document Understanding Processing model, not the Form Processing Model (for reasons explained above). Most people would agree that automation of documents and their classification is a good thing. But there are certain documents that make sense with Syntex, and some that don’t.
* Accounting and shipping documents are marked on both lists because these “semi-structured” documents could work quite well – or not, depending on layout consistency. It’s worth sandboxing with these documents as you build your AI models to see what results work for you.
As mentioned above, the Form Processing Model is great for AI usage to look at structured documents with layouts, but the difference between wanting it and enabling it is about $500 USD/month. This is no small cost to businesses operating on tight budgets. Additionally, the Form Processing Model is less of a structural integration into SharePoint than the Document Understanding Model – it’s handled by the PowerApps AI Builder instead, and doesn’t manage content types, content type columns, or the Power Automate part. You’d probably want to know exactly what you want to do with AI technology before committing to that kind of spend, especially if the Document Understanding Processing Model in Syntex can already handle most of your basic document automation needs.
So what really works and what doesn’t? I have sandboxed with SharePoint Syntex considerably since its release. Here’s what I’ve found as the rules of thumb:
Much like a car, you’ll need to maintain your models to get the best mileage – and keep driving in the right direction. Templates that have been adjusted over time (e.g. new layouts) may cause problems, and you may need to build a new model to handle new document layouts.
