Einstein Vision and Language

Building AI-enabled applications can be tough because you have to harness and make sense out of unstructured data. Like we mentioned in the first unit, there are so many types of unstructured data in files like images, text, videos, word documents, and audio files. But all businesses could benefit from predictions on this unstructured data, and this is where Einstein Vision and Language come in. Einstein Vision and Language are a set of APIs and services for Salesforce developers to use to add deep-learning capabilities to any application, ultimately allowing end users to classify images and extract meaning from text.

Einstein Vision consists of Einstein Object Detection and Einstein Image Classification. Together, these APIs harness and make sense out of unstructured data from images to help employees classify them at scale. Let’s say you own a camera company with a variety of products. More often than expected, equipment gets damaged. Reps at your business can take photos of the equipment, and with the help of Einstein Image Classification, they’d be able to understand whether the piece of equipment is damaged, where the damages are, and be given an estimate on how much it will cost to repair. This will take the guesswork out of inspecting all pieces of equipment, and it will save your reps a ton of time.

Einstein Object Detection extracts and contextualizes objects in images. For example, say you’re a company who has loads inventory in warehouses. Your teams can take photos of the inventory, and Einstein Object Detection can identify how many of certain items there are, so your team can accurately plan when to order more, saving on unnecessary spending.

Einstein Language consists of Einstein Sentiment and Einstein Intent. Together, these APIs harness and make sense out of unstructured data from text to help better understand your customers. Let’s say you work for a clothing company, and it has launched a new line of sweatshirts. You want to help your marketers understand how customers feel about your new line of sweatshirts. With Einstein Language, you can build an application that takes in information about the line of sweatshirts, like: what the sweatshirt line is called, what colors are included, what sizes are included, the materials, the locations it has been sold in, etc. Then, Einstein can surface through social media to see whether people post about the product and what is said about the product. Using positive and negative sentiment filters from Einstein Sentiment, your marketers understand who likes or dislikes the sweatshirts, and why they do, so that they can adjust their marketing tactics accordingly. Using Einstein Intent to categorize different text, your marketers can categorize what customers are saying about the product, whether they’re talking about the color, texture, durability, and more. This knowledge inherently your team become better marketers and better sellers.