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Architecting AI Solutions on Salesforce

You're reading from  Architecting AI Solutions on Salesforce

Product type Book
Published in Nov 2021
Publisher Packt
ISBN-13 9781801076012
Pages 340 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Lars Malmqvist Lars Malmqvist
Profile icon Lars Malmqvist

Table of Contents (17) Chapters

Preface 1. Section 1: Salesforce and AI
2. Chapter 1: AI Solutions on the Salesforce Einstein Platform 3. Section 2: Out-of-the-Box AI Features for Salesforce
4. Chapter 2: Salesforce AI for Sales 5. Chapter 3: Salesforce AI for Service 6. Chapter 4: Salesforce AI for Marketing and Commerce 7. Chapter 5: Salesforce AI for Industry Clouds 8. Section 3: Extending and Building AI Features
9. Chapter 6: Declarative Customization Options 10. Chapter 7: Building AI Features with Einstein Platform Services 11. Chapter 8: Integrating Third-Party AI Services 12. Section 4: Making the Right Decision
13. Chapter 9: A Salesforce AI Decision Guide 14. Chapter 10: Conclusion 15. Assessments 16. Other Books You May Enjoy

Using the power of built-in features

We started this book by looking at the built-in features in the core Salesforce clouds. No clouds are more used than Sales Cloud and Service Cloud, so it made sense to start our exploration there. What we saw was a range of pre-built features such as Einstein Lead Scoring, Einstein Forecasting, and Einstein Case Classification that use powerful and simple pre-built machine learning (ML) models to accomplish very specific tasks that help optimize sales or service processes.

In general, the lesson of the first few chapters is that there is a lot of value in the out-of-the-box features, and this can be realized quickly if these features happen to be a good fit for your business requirements and you don't have significant compliance or enterprise architecture constraints in terms of what you can implement. You can see a selection flow in the following diagram:

Figure 10.1 – Feature selection flow

Some features...

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