So you might have heard of Project Cortex, allowing you to auto-tag information in SharePoint and extract knowledge from your content. But what if you can't wait for the preview? Or you are in an on-premises scenario? You can use the Azure Cognitive services directly from your SharePoint on-premises environment! In this session, you will learn how you can extend your on-premises data in SharePoint with the different cognitive services Azure offers, including Azure Text Analytics and LUIS.

1. It was the best of times
Rutger

2. It was the worst of times
Albert-Jan

4. Using AI to classify your SharePoint Data
A love story

5. Cortex.
The next step in Knowledge in SharePoint through:
• Image and text recognition
• Form processing
• Machine teaching
To create knowledge entities through AI and experts
in the MMS. Providing a knowledge card within
content and a people card with knowledge. As well as
a topic page available through the knowledge center.

8. Form Recognizer.
Example

9. Our case.
• Our customer had a large set of unstructured
data (mainly Office and PDF files).
• All data was stored on a File share.
• The data was not searchable, no full text
search was configured.
• No metadata was captured and most of the
files where scans of typewriter created data.
• Legal requirements prevented us of putting
the full data-set in the cloud.

10. Unstructured data.

11. Unstructured data.

12. Unstructured data.

13. So how does it work.
Crawl
SharePoint 2019
Users
Content Processing Index
Document Parsing Content Enrichment Word breaking Custom Entity Extraction
Site Collection
Network share
App Server Cloud
Webservice Metadata extraction Data Cleansing
LUIS Training Model
LUIS intents & entities

14. So how does it work.
Crawl
SharePoint 2019
Users
Content Processing Index
Document Parsing Content Enrichment Word breaking Custom Entity Extraction
Site Collection
Network share
App Server Cloud
Webservice Metadata extraction Data Cleansing
LUIS Training Model
LUIS intents & entities
SharePoint provides us
with Full Text Search
Custom Content
Processing allows us to
inject intelligence in the
search process
Our ‘logic’ can
determine what can be
send to the cloud.
LUIS provides intents
and entities that can be
written back to our
search results

15. LUIS.
Utterance
What a user says
Intent
What a user means
Entities
What you want to extract

18. What would we do differently.
1. We scored between 80% to 95% of auto tagging with
our data set after just 10 days. We are not data
scientists so we could do better.
2. We would love to extract more data, not only from the
files you are processing but also from other back-end
systems. When we retrieve a project number from a file,
we can use that to gather the PM from ERP.
3. Train in the cloud, run on-premises (locally run Docker
with LUIS or Text-Analyser trained in the cloud would
allow us to analyze even more text!

19. Thank you.
Reach out for questions!
• Rutger Knijnenburg • Albert-Jan Schot
Technical Cloud Consultant
@knijnOps
knijnops.com
CTO & MVP
@appieschot
cloudappie.nl