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The move comes as the demand for generative AI tooling continues to grow in the enterprise context. Salesforce says it will help companies build automations faster to deliver personalized experiences to their end customers.
However, the integrations are not yet live as the company is planning to roll them out gradually as part of a pilot program.
How will Einstein GPT and data cloud help?
Einstein GPT is Salesforce’s generative AI assistant that delivers more than 200 billion AI-powered predictions per day across customer 360. Meanwhile, data cloud is the company’s data warehouse platform that brings together data points from different sources to host unified customer profiles in real time.
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By connecting the two products with flow, Salesforce is giving enterprises the ability to use natural language prompts to create automated workflows that trigger actions based on real-time data signals.
“By powering flow with Einstein GPT and data cloud, we’re not only enhancing usability, but ensuring our customers have access to the most advanced tools to achieve even more productivity, efficiency, and growth,” said John Kucera, SVP of automation at Salesforce. “This democratizes enterprise AI for everyone.”
Einstein GPT handles the workflow creation bit, allowing both technical and non-technical users to create and modify automations using a conversational interface. Meanwhile, the data cloud helps execute the said workflows by tracking real-time changes and triggering the required actions.
For example, a marketer could type in the request to build an automation flow (with a desired action) for when a customer abandons their cart. The system will build the workflow in near real-time and trigger the desired action, such as sending a personalized message with a promo code, as and when it detects that a customer has dropped out of their cart.
Numerous other capabilities
The same approach would also work for use cases like managing inventory, product pricing, fraud detection, patient monitoring and machine maintenance, Salesforce said.
“There is a lot of potential in using generative AI like Einstein GPT with Flow,” Kyle Davis, VP analyst at Gartner, told VentureBeat. “For one, it allows less technical users to use natural language to design automation. There is still the need to validate what is being generated, but validation is easier than designing a flow from scratch.”
“Integrating data cloud and flow is critical to the success of both services,” David added. “Data cloud provides the ability to ingest and harmonize Salesforce and external data. While this is important, acting against this data has even more value to customers. This is what the integration of data cloud with Flow offers.”
Beta release in June
While both integrations are currently in the development phase, Salesforce expects them to go into early beta in June 2023, followed by a broader public release next year. The company says it will soon announce dates for the pilot program.
“We want to make this as broadly accessible to our customers as possible,” the company noted.
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