Architecting AI Solutions on Salesforce: Design powerful and accurate AI-driven state-of-the-art solutions tailor-made for modern business demands

Use Salesforce's out-of-the-box and advanced integration-based AI capabilities to architect modern enterprise solutions on sales, service, marketing, and commerce clouds to drive digital innovation for your clients

Key Features

• Get up to speed with Salesforce's AI features and capabilities to meet ever-evolving client needs
• Get expert advice on key architectural decisions and trade-offs when designing AI-driven Salesforce solutions
• Integrate third-party AI services into applications that modernize your solutions

Book Description

The ever-increasing need for designing state-of-the-art solutions using AI features requires a sound understanding of a vast array of AI capabilities that help you to architect modern solutions. Salesforce Einstein is a set of services that allows seamless implementation of advanced artificial intelligence (AI) features while retaining the ability to cater to custom requirements for the business.

This book will help you understand the business and technical benefits of building AI solutions and components available in Salesforce. As you work through a case study of a fictional company beginning to adopt AI in its Salesforce ecosystem, 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 Salesforce book concludes by taking 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 architect Salesforce AI solutions to meet various customer requirements confidently.

What you will learn

• Explore the AI components available in Salesforce and the architectural model for Salesforce Einstein
• Extend the out-of-the-box features using Einstein Services on major Salesforce clouds
• Use Einstein declarative features to create your custom solutions with the right approach
• Architect AI solutions on marketing, commerce, and industry clouds
• Use Salesforce Einstein Platform Services APIs to create custom AI solutions
• Integrate third-party AI services such as Microsoft Cognitive Services and Amazon SageMaker into Salesforce

Who this book is for

This book is for existing and aspiring technical and functional architects, technical decision-makers working on the Salesforce ecosystem, and those responsible for designing AI solutions in their Salesforce ecosystem. Lead and senior Salesforce developers who want to start their Salesforce architecture journey will also find this book helpful. Working knowledge of the Salesforce platform is necessary to get the most out of this book.

Table of Contents

1. AI Solutions on the Salesforce Einstein Platform
2. Salesforce AI for Sales
3. Salesforce AI for Service
4. Salesforce AI for Marketing and Commerce
5. Salesforce AI for Industry Clouds
6. Declarative Customization Options
7. Building AI Features with Einstein Platform Services
8. Integrating Third-Party AI Services
9. A Salesforce AI Decision Guide
10. Conclusion

Lars Malmqvist has spent the past 12 years working as an architect and CTO within the Salesforce ecosystem. For the past 5 years, he has been particularly focusing on advanced AI solutions. He has worked on over 40 Salesforce implementations, ranging from simple out-of-the-box scenarios to advanced, bespoke, multi-cloud solutions for large global brands. He is a 23x certified Salesforce CTA with degrees in computer science, mathematics, and technology management and an MBA from the University of Cambridge. Currently, he works as a senior manager at Accenture and is in the final stages of completing a PhD with a focus on deep learning.