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Salesforce Announces Einstein GPT Integration with Flow + Data Cloud

By Andrew Cook

Salesforce has today announced new Einstein GPT and real Data Cloud capabilities for Flow, its portfolio of automation tools.

This news brings the power of Einstein GPT and Data Cloud to the everyday admin, making it much easier for businesses to leverage these technologies. Previously, you would need a team of engineers to be able to leverage mass amounts of data and build automations off the back of them. Being able to do this in real-time (with clicks, not code) truly is groundbreaking.

What Is Einstein GPT?

Before talking about Einstein GPT, we first need to mention ChatGPT. ChatGPT is a natural language processing tool driven by AI technology, which was launched in November 2022 by OpenAI.

Salesforce then announced Einstein GPT at TrailblazerDX ‘23, which builds on the ChatGPT technology. Einstein GPT combines public and private AI models with CRM data so that users can ask natural-language prompts (i.e. conversational questions) directly within Salesforce CRM. The result? AI-generated content is delivered that continuously adapts to changing customer information and needs – hugely time-saving for users. 

The beauty of Einstein GPT is that it’s always learning based on what users put into it; as Salesforce are building out their initial model, they will be training Einstein GPT based on what they are putting into it. This enables Einstein GPT to learn and adhere to best practices, as it will have been trained to learn them.

Einstein GPT for Flow

Salesforce Flow empowers you to build complex business solutions using clicks, not code. Flow Builder is the most powerful tool a Salesforce Admin has at their disposal, as it provides similar powers as Salesforce Developers.

Combining Einstein GPT with Flow, users can create and modify automations using a conversational interface, which radically simplifies the flow creation process and significantly lowers barriers for non-technical users. This will make the overall experience with Flow Builder much more simple, and allow those who are less technical to create far more powerful automations. And all while adhering to best practices which are more important than ever with the new capabilities of Flow Builder.

With Einstein GPT for Flow, you will be able to take advantage of the following:

  • Describe what kind of flow you want to build and see it built for you in near real-time.
  • Describe a formula you want and Einstein GPT will build it automatically.
  • See improved searchability by describing a function you need to locate and have Einstein GPT insert the correct flow automatically – instead of having to seek out sub-flows and invocable actions.

Pricing for all Einstein GPT products is to be confirmed. However, Salesforce will soon announce dates for the pilot program, which they will want to make as broadly accessible to their customers as possible.

Data Cloud for Flow

Announced at Dreamforce 2022, Salesforce Data Cloud (previously Genie), paves the way for highly personalized customer experiences, delivered in real-time. It’s your command center for everything about the customer. Data Cloud ingests and stores real-time data streams at massive scale, and combines it with your Salesforce data.

By powering Flow with Data Cloud – which connects, harmonizes, and unifies all of a company’s data in real-time in a single, real-time customer profile – customers can now automate complex workflows and trigger actions based on real-time changes.

MuleSoft’s report revealed that 36% of IT time is spent designing, building, and testing custom integrations. With Data Cloud for Flow, this is something that can be done by an admin with clicks, not code. With the average company having 976 different applications, being able to see, connect, harmonize, and unify the data from these is vitally important to get a complete picture of your customers.

With Data Cloud’s built-in connectors, you can bring in data from any source, including Salesforce apps, mobile, web, connected devices, and even from legacy systems with MuleSoft and historical data from proprietary data lakes – all in real-time. 

Coupled with Flow, this allows customers to automate complex workflows and trigger actions based on real-time changes – previously, this was only available to organizations with massive engineering resources. This will help companies make every experience feel interconnected and personalized for their customers.

There are many examples of how Data Cloud for Flow can be leveraged to help your company create experiences for your customers that feel interconnected and personalized:

  • Marketers use automation powered by real-time telemetry data to optimize the retail experience by offering in-store discounts at the right moment.
  • Commerce professionals use real-time data to power dynamic pricing in eCommerce by automatically adjusting prices based on real-time demand and supply – as well as updating inventory levels and availability information.
  • Financial service companies use real-time data to automate fraud detection and prevention by flagging suspicious transactions based on unusual patterns, such as large withdrawals or transfers to foreign countries.
  • Manufacturing companies use real-time data to optimize production processes and efficiency by monitoring machine performance in real-time to trigger automated maintenance requests.


These are two announcements that are hard to ignore. Personally, I don’t get excited by data. Everything we do these days is run based on data; from our phones to our cars, data plays a part in some way. Yet it still isn’t a sexy topic! One reason for this may be the expertise required to truly leverage data and understand it. Data Cloud for Flow can potentially change that, as it may revolutionize our relationship with data overall.

Then there’s Einstein GPT for Flow. A lot has been said about the importance of building automations in Flow, with the retirement of both Workflow Rules and Process Builder imminent. This tool will make it so much easier to build complex automations within Salesforce, all while adhering to Salesforce best practices (which sometimes get overlooked). I, for one, am extremely excited to try out both of these new features and see what they can really do. I’ve got a feeling I’m not the only one.

The Author

Andrew Cook

Andrew is a Salesforce Technical Instructor at Salesforce Ben. He is 14x certified and has worked in the ecosystem for 12 years.

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