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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

Introducing Einstein declarative features

In this chapter, we change gears again. So far, we have primarily been looking at features that come out of the box with various Salesforce clouds. We've had to do some configuration, but nothing particularly strenuous. Mostly, things work out of the box.

While that can be a great strength, it also means that when you hit the limits, they are hard. Typically, you can't bend a feature to match requirements, even though, technically, the requirements are quite close to the core functionality.

Once you hit the limit, your next port of call should be to see if you can meet your requirements using some combination of declarative features to avoid the overhead of having to use code and train your own models. Powerful as such solutions might be, they are also more expensive, higher-maintenance, and riskier than declarative solutions.

In this chapter, we will go through three features of the Einstein platform that can help you create...

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