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Evolution of Salesforce Einstein AI

By |2020-07-29T05:38:07+00:00September 3rd, 2019|

Introduction:

There is a lot of talk around Enterprise AI i.e. using AI at the enterprise level particularly in areas such as Customer Service and Marketing. Salesforce (Einstein.ai) is researching and enhancing the capabilities in 3 different fields: Vision, Language, and Voice.

Vision

Vision can be used for:

  • Visual Description
  • Visual Question Answering
  • Visual Object Detection

Einstein Vision Rest APIs used:

  • Einstein Image Classification (Categorize Image at scale)
  • Einstein Object Detection (Extract and Contextualize objects in images)

Some applicable Business Use Cases:

  • Social Media – Out of the box Solution for Image-based brand recognition
  • Sales & Service – Visual Identification of Products and Parts to streamline the sales and service processes.
  • Insurance – Automated Insurance claims by identification of damaged parts and severity
  • Retail – Product Identification for field sales teams to streamline in-store audits.

Language:

NLP consists of both Natural Language Understanding (NLU) and Natural Language Generation. Salesforce is advancing in all the top Natural Language Processing (NLP) tasks:

  • Natural Language Inference
  • Sentiment Analysis
  • Zero-Shot Relation Extraction
  • Question Answering
  • Machine Translation
  • Common-Sense pronoun Resolution
  • Semantic Parsing
  • Goal-Oriented Dialogue
  • Summarization
  • Semantic Role Labelling

Unlocking Language Breakthroughs with Multi-Task NLP

Multi-task learning is a subfield of machine learning in which multiple learning tasks are solved at the same time. Some use cases:

  • Model Optimization (Continuous improvement with each answered question)
  • Zero-Shot Learning (Ability for machines to adapt to new domains and learn new tasks without specific training)
    General Language Understanding (Adaptable to slight variations in questions and tasks and can generalize to unseen classes).

Einstein Language Rest APIs used:

  • Einstein Sentiment (Classify text as negative, positive or neutral)
  • Einstein Intent (Classify underlying intent in a body of text)

Some applicable Business Use Cases:

  • Seamless Support – (In-Service industry) using Salesforce Einstein Chatbots
  • Actionable Notes – Taking notes using Einstein Voice Assistant leveraging NLP services
  • Automatic Triage – Automatic Triaging of cases, when a case comes in, understanding the intent and routing it to the right department
  • Survey Analysis – Analysing surveys and the sentiment in the surveys

Vision:

  • Einstein Voice Assistant is the product to watch for in this field
  • Currently voice tech. integration is available in services/applications and eventually, it will be available as APIs in similar ways like Vision and Language.

Resources available today:

Let us look at the resources available today to work with Einstein AI.

  • Most of the API can be UI-driven; such packages are available on AppExchange for download. This can be used as a point and click instead of code.salesforce einstein
  • There is a feedback API as well, to ensure the model is improving over time.
  • Free Sign up (till 2000 calls per month) & Documentation: eisntein.ai/products
  • Model Builder: sfdc.co/ModelBuilder
  • Resources for getting started:
  • Beginner: sfdc.co/VizLangOverview
  • Intermediate: sfdc.co/ObjectDetection
  • Learn more about Salesforce Research at “Einstein.ai”

Einstein Capabilitiesevolution of salesforce einstein

  • These are more than 35 Einstein capabilities that are now live. Every Salesforce Cloud has some AI, either baked into it or that you can buy. Some of the examples are given in the next couple of sections. Salesforce says that its strategy is to Featurize, Productize, and Appize the Einstein features that they are trying to build. These should be either available directly from the salesforce platform or will be available in API services so that they can be consumed directly.
  • All the different capabilities that Einstein has been made up of a mix of 6 main ingredients:
  • Yes/No Predictions (most used one in SF Einstein)
  • Numeric Predictions
  • Classifications
  • Recommendations
  • Voice
  • Workflow & Rules

Einstein for Sales:

The following use cases are considered to assist Sales teams:

  • Lead Scoring
  • Opportunity Scoring
  • Einstein Prediction builder (enables use cases for Top Predictive Factors for an object)
    Einstein Forecasting – Tells if this individual deal on a macro scale is going to close or not, how much is it going to close for and when I roll them all up, where am I going to end up at the end of the quarter or at the end of this month.

Einstein for Service:

The following use cases are considered to assist Service teams:

  • Case Classification/Categorization for automated routing
  • Next Best Action
  • Einstein Bots
  • Omni Channel Routing with real-time scoring for case assignment

Einstein for Marketing:

The following use cases are considered to assist Marketing teams:

  • Email Engagement Prediction
  • Email Open Prediction
  • Email Click Prediction
  • Web Conversion Prediction
  • Subscriber Retention Prediction

These are included in the top two Salesforce Org Marketing Cloud editions.

einstein ai evolution
Einstein Platform Services:

Various capabilities are included as a part of Einstein Platform Services. They help to deploy Einstein capabilities in APEX Code or Lightning Web Components:

  • Einstein Translation (in beta)
  • Einstein OCR (in beta)
  • AI Learning Loop enables Smarter recommendations (add-on top of Next Best Thing)
    Next Best Action (free till 5000 requests)
  • Einstein Prediction Builder

Seems like all of this is just the tip of the iceberg. Salesforce has a lot more coming up for their fans. Salesforce with Einstein is going to make businesses more and more productive. We all will be waiting for future releases that would enable and open new solutions and offerings in multiple domains.

8 Comments

  1. albertson August 1, 2020 at 12:42 am - Reply

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    • Mirketa Inc September 2, 2020 at 6:31 am - Reply

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    • Mirketa Inc September 2, 2020 at 6:32 am - Reply

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