SharePoint Syntex Page 1 Contoso Corporation uses SharePoint to store a huge variety of documents, from sales and marketing to HR and Operations. Now they’re implementing SharePoint Syntex to automatically capture knowledge from business documents and use that to drive understanding and enrich automation across the company. In this demo, Megan Bowen, an HR Manager at Contoso, will train SharePoint Syntex to recognize a common Contoso HR document, automatically extract useful information from it and store that data. Page 2 Megan Bowen, an HR manager at Contoso, is going to create a document understanding model that will process a typical HR document and extract key terms. Page 3 A document understanding model uses artificial intelligence (AI) to automatically classify documents and extract useful information Page 4 A document understanding model uses artificial intelligence (AI) to automatically classify documents and extract useful information.
SharePoint Syntex Page 1
Contoso Corporation uses SharePoint to store a huge variety of
documents, from sales and marketing to HR and Operations. Now
they’re implementing SharePoint Syntex to automatically capture
knowledge from business documents and use that to drive
understanding and enrich automation across the company.
In this demo, Megan Bowen, an HR Manager at Contoso, will train
SharePoint Syntex to recognize a common Contoso HR document,
automatically extract useful information from it and store that
data.
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Megan Bowen, an HR manager at Contoso, is going to create a
document understanding model that will process a typical HR
document and extract key terms.
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Today, Megan is going to train the AI to recognize insurance
benefit change letters. This is a common document that Contoso is
required to send when employees’ "insurance benefits change". She
makes this a new content type in SharePoint. She could also create
a model linked to an existing content type.
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Megan can also configure the model to automatically apply the
correct document retention policies whenever a document of this
type is identified. This will greatly simplify compliance for
Megan’s department.
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Now Megan creates the model. She can also use Syntex to extract and
process structured content, such as forms.
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Syntex uses AI, trained on existing documents in order to classify
and recognize similar documents in the future.
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To begin this process, Megan uploads several sample documents for
training.
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The training documents include several examples of benefit change
letters, as well as some other HR documents that aren’t benefit
letters to provide contrast.
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Megan now creates a classifier to identify if an entire document
belongs or does not belong to a specific content type.
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She goes through each document in the training set and marks all
the ones that are benefit change letters.
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The last two documents are not benefit letters. Megan marks them as
such.
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Finally, she adds an explanation to help define information in
Syntex.
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Here, Megan uses the phrase Benefit Change Notice, which appears in
all the benefit letters, to help identify them.
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When she’s done, Megan can see that the classifier has processed
each training document and training is complete.
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Now Megan will create an extractor to identify and pull a specific
piece of information from the document—in this case, the insurance
provider.
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The extractor will save this information to a new column in a
SharePoint library, for easier discovery and use.
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Megan trains the AI to recognize the insurance provider name. In
each document, she highlights the information she wants to
extract.
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The last two documents are negative examples and do not include the
information that Megan wants to extract.
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When she’s done, Megan reviews the results to see how the extractor
preforms. It catches most of the providers, but she can see the
extractor didn’t fully capture one of the providers, Best for you
Organics.
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With both the classifier and extractor working as desired, Megan is
ready to apply this model to a library.
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When applied to a library, the model will automatically process
every document added to the library.
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If the document fits the classification, the relevant information
is extracted and stored in a SharePoint column.
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To test her model, Megan uploads some more benefit change
letters.
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After a few moments, Syntex has successfully identified them as
benefit change letters and extracted the insurance provider for
each one.
SharePoint Syntex helps organizations like Contoso transform
content into knowledge and automate content processing using
advanced AI and machine learning combined with human
experience.
SharePoint Syntex
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