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chaitanyank_sap
Participant
Hello Experts,

What makes business successful?

Well, it's a million-dollar question. 🙂

Many experts were successful to answer by considering facts with different
strategies. I am sure about the factors, which can help business
to take smart decisions based on data.

SAP Conversational AI Chatbots will ease process of accessing complex data to all relevant stakeholders to make decisions. Many Professionals from each team have to spend their time following exhaustive process to get data or to feed data manually in the system.

SAP Conversational AI Chatbot will open new opportunities to integrate with different applications. It can read unstructured requests and facilitate user’s with required data avoiding Exhaustive process.

Agenda:

Myself & kunjshukla has been working on SAP Conversational AI Chatbots for a while and want to share one of the interesting use case in which, we will do an end to end integration from the S/4 Hana system to SAP Conversational AI Chatbot and then access the chatbot from the MS Teams.

Introduction:

This article is part of a series of learning, with bunch of tutorials explaining to create SAP Conversational AI Chatbot and to provide access to business data by using Microsoft Teams. We are going to create a SAP Conversational AI Chatbot and integrate it with SAP S/4HANA to access SAP business data.
Eg : Sales order data/ Purchase Order from SAP S/4HANA system to be exposed to the user in simplified way.

Let’s begin…

The below topics will be covered as part of the blog series:

•  SAP S/4HANA integration with SAP Conversational AI Chatbot & MS Teams App Studio.
•  Create a CDS view to be exposed as an OData Service
•  Cloud connector configuration & Introduction to SAP Conversational AI Chatbot
•  Consume it in SAP SAP Business Technology Platform to create a Public API with detailed  explanation on the node.js
•  Consume the Public API in the SAP Conversational AI Chatbot to create Chatbot
•  Consume the SAP Conversational AI Chatbot in the MS Teams

High Level Architecture flow :



SAP S/4HANA Integration with SAP Conversational AI Chatbot and MS Teams using MS App Studio


 

Small Demonstration :



 

Components Involved:

1. SAP S/4HANA System (S14)
a. Serves as the data source
2. SAP Cloud Connector (local installation)
a. Serves as a link between SAP Cloud Platform applications and on-premise systems
3. SAP Cloud Platform Cloud Foundry ( trial Account)
a. Provide us access to Destination and connectivity service
b. Hosts Nodejs application which exposes the OData service as Public API
4. Community edition of SAP Conversational AI Chatbot
a. Consumes the Public API in the SAP Conversational AI Chatbot
b. SAP Conversational AI Chatbot can be easily integrated with various channel e.g. MS Teams
5. Channels: MS Teams and SAP Fiori
a. Channels using which users can access the SAP Conversational AI Chatbot

Solution Explanation:

  • Create a CDS View which in turn is exposed as an OData service/ use Standard OData Service.

  • The OData service is consumed in the SAP cloud platform via the SAP cloud connector.

  • Using node.js application hosted on SCP Cloud foundry, we expose our OData service
    to the internet.

  • Node.js application is hosted on the SCP Cloud foundry and act as a middle ware as it
    facilitates communication between the SAP S/4HANA system and SAP Conversation AI chatbot.

  • Community edition of the SAP Conversational AI should have public access to your API.

  • Public APIs as provided by the node.js application is used in the SAP conversational AI chat bot.

  • SAP Conversational AI Chatbot can be queried for any business-related data. The query will be routed from node.js application (deployed on SAP cloud platform) to SAP S/4HANA via SAP cloud connector, using a secure tunnel to communicate.

  • The SAP conversational AI chat bot is then integrated with Microsoft teams, where the user can access chat bot.


Conclusion:

We are done with the High level Architecture overview in this blog post, It's time to get into action. We will come up with follow-up blog posts very soon.

Feedback :

Thanks for taking your time to go through this article, we hope you liked the content. We would appreciate if you can spare few minutes to leave us feedback on your experience.
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