Salesforce announced the name change of its Einstein 1 Data Cloud and new features for the Einstein generative AI assistant for CRM at the Dreamforce conference in San Francisco on Tuesday, September 12.
Salesforce’s Einstein 1 Data Cloud metadata framework will be integrated into the Einstein 1 platform. The CRM giant also plans expanded capabilities for the Einstein GPT generative AI assistant, launched in March, under the Einstein Platform umbrella. 1.
Data Cloud integrates with the Einstein 1 platform
Einstein 1 is “a relaunch of our Salesforce platform to create a trusted AI platform for our enterprise customers,” Patrick Stokes, executive vice president of product and industry marketing at Salesforce, said in a pre-Dreamforce press briefing. (Figure A). The Einstein 1 platform contains all of Salesforce’s customer data, enabling generative AI capabilities to learn and generate new content from this data.
Einstein 1 unifies data into a single customer record for use across the entire Salesforce platform, including Sales Cloud, Service Cloud, Marketing Cloud, and Commerce Cloud.
Helping businesses use the data they already have
Combining different Salesforce cloud products under the Einstein 1 name allows companies to find uses for the data they already collect, said Muralidhar Krishnaprasad, executive vice president of engineering at Salesforce Marketing Cloud, in an interview with TechRepublic.
“We think of CRM and AI data as a loop,” Krishnaprasad said. “Your CRM (and) your engagement (with) your customers will be better if you use AI more, especially generative AI. You can have personalized experiences, but this AI is only good if you have the right data.
“We see this as a cycle where CRM generates a lot of data and other business data. You mix that up, you use AI to generate the right personalized things, (and) you feed that back into your engagement,” he said.
In a press release, Parker Harris, co-founder and chief technology officer at Salesforce, discussed how data and AI can work together.
“We pioneered the metadata framework almost 25 years ago to seamlessly link data across applications. It’s the connective tissue that fuels innovation,” Harris said. “Now, with Data Cloud and native Einstein AI on the Einstein 1 platform, businesses can easily create AI-powered applications and workflows that improve productivity, reduce costs, and deliver incredible customer experiences.” »
Salesforce Introduces Einstein Copilot Generative AI Assistant
Salesforce is joining the AI assistant trend with Einstein Copilot, a natural language chatbot that will be integrated into every Salesforce application. Einstein Copilot can help sales, service, or commerce employees write emails, prepare for meetings, handle customer calls, or generate the right Tableau dashboards; It does this by using an organization’s customer data stored in Salesforce Data Cloud.
“It’s really about moving from just clicking through the navigation to get to the information you’re looking for… to just being able to ask for it in natural language,” said Clara Shih, general manager of Salesforce AI, during from a press briefing.
The Einstein platform already builds on 10 years of innovation based on predictive capabilities, Stokes said.
“We wanted to get our foot in the door and see how well it would work and what kind of data we would need to connect to the prompt to provide useful generation (generative content),” Stokes said.
Copilot was born from this lineage, but it is different because it can respond in natural language and a conversational style and integrates into Sales Cloud and Service Cloud dashboards. Einstein Copilot can interpret Tableau data, help sales staff close deals, summarize content, transform natural language instructions into code in the Apex programming language, and compose emails.
Einstein Copilot will be available to all Salesforce users across all clouds, extending the capabilities of Einstein GPT.
Einstein Copilot Studio lets organizations personalize AI generative content
The Einstein Copilot administration portal will be Einstein Copilot Studio, through which organizations will be able to customize the chatbot based on their specific prompts, skills and AI models (Figure B).
Einstein Copilot Studio is made up of three main sets of tools: Prompt Builder, Skills Builder, and Model Builder. The tools will help Salesforce customers tailor their AI-powered communications to their brand needs and voice.
- Prompt Builder adds customizations and can A/B test versions before rolling them out to the service team.
- In Skills Builder, company administrators can control and designate which workflows they want the co-pilot to be able to access. Companies that already have customer workflows on Salesforce will be able to select them in Skills Builder.
- Model Builder allows companies to bring their own AI model (from Anthropic, Cohere, Databricks, Vertex AI, or OpenAI from Google Cloud) or use one of Salesforce’s large proprietary language models. In any case, the selected models can be trained on Data Cloud.
Einstein Trust Layer addresses security concerns
Salesforce announced during the press conference that Einstein Copilot and Copilot Studio will work together with Einstein Trust Layer, a Salesforce-native AI architecture designed to secure first-party information. The Einstein Trust Layer was first announced in June.
The Einstein trust layer ensures that no customer data is used for training large language models. It prevents toxicity, hides personally identifiable information, and creates an auditable data trail of what Einstein Copilot does.
SEE: Salesforce’s guidelines for reducing AI bias (TechRepublic)
The trust layer includes information on whether AI-generated emails actually help businesses improve. For example, if salespeople or service workers tend to ask AI to generate content, but then heavily edit or don’t use that content, the trust layer is where administrators can access this information and refine the AI based on how Einstein Copilot is used. used in the real world.
“We are constantly experimenting with the right models to use for the right job, which versions to use and also (how to) optimize costs,” Krishnaprasad said. For example, it’s important to let administrators know when AI isn’t being used so they can change temperature settings or make other adjustments to make the result more appealing.
Krishnaprasad noted that companies looking to get started with generative AI should ask themselves if they already have the right data. Data is essential because it allows generative AI to personalize responses.
Krishnaprasad said potential buyers of generative AI should ask themselves:
- “Where should I place my generative AI?
- “How much data should I expose? »
- “What brand voice do I want for this?” »
Business leaders looking to use generative AI should experiment and optimize, which the trust layer allows them to do, Krishnaprasad added.
“Look at the reviews, because what you think is the right thing may not be what your consumers think is the right thing,” he said.
When will Einstein Copilot, Einstein Copilot Studio, and Einstein Trust Layer be available?
Einstein Copilot, Copilot Studio and Trust Layer will be tested this fall as pilot tests, Salesforce said. A general availability date has not yet been announced.