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Architecting AI Solutions on Salesforce

Architecting AI Solutions on Salesforce

By : Lars Malmqvist
4.8 (13)
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Architecting AI Solutions on Salesforce

Architecting AI Solutions on Salesforce

4.8 (13)
By: Lars Malmqvist

Overview of this book

Written for Salesforce architects who want quickly implementable AI solutions for their business challenges, Architecting AI Solutions on Salesforce is a shortcut to understanding Salesforce Einstein’s full capabilities – and using them. To illustrate the full technical benefits of Salesforce’s own AI solutions and components, this book will take you through a case study of a fictional company beginning to adopt AI in its Salesforce ecosystem. As you progress, you'll learn how to configure and extend the out-of-the-box features on various Salesforce clouds, their pros, cons, and limitations. You'll also discover how to extend these features using on- and off-platform choices and how to make the best architectural choices when designing custom solutions. Later, you'll advance to integrating third-party AI services such as the Google Translation API, Microsoft Cognitive Services, and Amazon SageMaker on top of your existing solutions. This isn’t a beginners’ Salesforce book, but a comprehensive overview with practical examples that will also take you through key architectural decisions and trade-offs that may impact the design choices you make. By the end of this book, you'll be able to use Salesforce to design powerful tailor-made solutions for your customers with confidence.
Table of Contents (17 chapters)
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1
Section 1: Salesforce and AI
3
Section 2: Out-of-the-Box AI Features for Salesforce
8
Section 3: Extending and Building AI Features
12
Section 4: Making the Right Decision

Summary

In this chapter, we have looked at some of the key parts of the Salesforce Einstein platform, including elements from the Sales Cloud Einstein and High Velocity Sales offerings. We started by learning about Lead Scoring and Opportunity Scoring, which deliver an easy-to-deploy ML-based model for judging the quality of leads and opportunities. We saw in detail how to configure this feature, which is a good representation of the typical flow for configuring out-of-the-box Einstein features.

Then, we reviewed Einstein Forecasting, an automated ML-based forecasting model, which uses your historical opportunity data to generate a prediction of whether your current sales efforts are on track.

We then devoted considerable time to exploring Einstein Activity Capture, a nifty feature that can save sales reps a lot of time entering data into the CRM by automatically matching email, contact, and event data from users' emails and calendars to the relevant records in Salesforce...

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