Newspatrolling.com News cum Content Syndication Portal Online
Salesforce admins and developers can now build, customize, and embed AI across every Salesforce app and workflow, including Einstein Copilot
Einstein 1 Studio is deeply integrated with Data Cloud, which unlocks and unifies trapped data and grounds AI models with a comprehensive understanding of customer data and metadata
New Trailhead AI courses — including Einstein Copilot and Prompt Builder — introduce career pathways and skills for over 6 million Trailblazers on Salesforce’s free online learning platform
San Francisco – March 7, 2024 – Today at TrailblazerDX, Salesforce’s developer conference, Salesforce (NYSE: CRM) announced the availability of Einstein 1 Studio, a set of low-code tools that enables Salesforce admins and developers to customize Einstein Copilot — the conversational AI assistant for CRM — and seamlessly embed AI across any app for every customer and employee experience.
Einstein 1 Studio includes Copilot Builder for creating custom AI actions to accomplish specific business tasks, Prompt Builder for building and activating custom prompts in the flow of work, and Model Builder, where users can build or import a variety of AI models. This enables businesses to deliver trusted AI experiences across Salesforce’s Einstein 1 Platform that are tailored to their customers’ needs.
[Caption: Introducing Einstein 1 Studio]Why it matters: Enterprises face critical challenges in unlocking the power of AI across their business, with 9 in 10 IT professionals saying generative AI has forced them to change the way new technology is implemented and used. They need intuitive user interfaces that make it easy to interact with AI in the flow of work; AI models to fit their use cases; and access to trusted customer and business data to ground the AI models and ensure accurate, relevant outputs.
Salesforce’s Einstein 1 Platform integrates the user interface, a variety of AI models, and data in a single metadata-driven platform. This is what powers Einstein 1 Studio’s tools, facilitating low-code and no-code customization of Einstein Copilot, as well as building and modifying embedded prompts and actions that seamlessly connect to AI models in the flow of work across every Salesforce app. Einstein 1 Studio is deeply integrated with Data Cloud, which safely unlocks and unifies trapped data and grounds AI models with a comprehensive understanding of customers’ data and metadata.
Go deeper with Einstein 1 Studio: Salesforce admins and developers can use the following new Einstein 1 Studio tools to build the next generation of AI applications by customizing AI across every Salesforce app and workflow. This will help companies boost productivity, improve customer experiences, and increase margins. The tools include:
Copilot Builder: Create AI actions to accomplish business tasks (beta) — Copilot Builder helps every company configure and customize Einstein Copilot for their business. Salesforce admins and developers can use tools they already have, like Apex, Flow, and MuleSoft APIs, and new generative AI components like prompts, to enable
Einstein Copilot to complete tasks in the flow of work. Einstein Copilot can leverage these custom actions to complete tasks across any Salesforce application or external system.
Prompt Builder: Craft custom and trusted AI prompts with ease (GA) —
Prompt Builder empowers admins and developers to create custom, reusable AI prompts without coding, simplifying complex processes and driving business innovation. This not only broadens the use of generative AI beyond conversational interfaces, but also allows customers to design and repurpose prompts for use across other experiences. For example, a custom prompt can be seamlessly embedded in a contact record as a button, enabling an agent in the contact center to get a snapshot of all escalated cases for a customer in one click.
Model Builder: Choose an LLM or build an AI model based on the job to be done (GA) — Unlike other solutions that limit businesses to a single Large Language Model (LLM), Einstein 1 Studio provides the flexibility to connect to a variety of AI models. Additionally, Model Builder is a no-code, low-code, and pro-code way for companies to build their own predictive AI models, trained on their Data Cloud data. For generative AI, Model Builder allows customers to select from LLMs managed by Salesforce, or bring their own models. Businesses can use predictive and generative AI models and services from Salesforce partners, including Amazon Web Services (AWS) via.
Amazon Bedrock and Amazon SageMaker, Anthropic, Azure OpenAI, Cohere, Databricks, Google Cloud’s Vertex AI, and OpenAI, and train or fine-tune select models on Data Cloud data without moving or copying data.
Einstein Trust Layer: Deploy AI you can trust, on your terms: Designed for enterprise AI, the Einstein Trust Layer is a collection of features that help companies benefit from generative AI without compromising security or safety standards. New to the Einstein Trust Layer is customer-configured data masking, enabling admins to select the fields they want to mask, providing greater control. Additionally, the audit trail and feedback data collected from AI prompts and responses is now stored in Data Cloud, where it can be easily reported on or used for automated alerts through Flow and other Einstein 1 Platform tools.
Salesforce perspective: “Customers have always loved how easy it is to customize Salesforce. Our new Einstein 1 Studio makes it easy for admins and developers to build and customize Einstein Copilot and embed AI apps in the flow of work within Salesforce, tailored to the specific requirements of their company and industry,” said Clara Shih, CEO of Salesforce AI. “Built on our Einstein 1 Platform and unified by metadata that safely connects and unlocks data from across an enterprise, Einstein 1 Studio’s low-code tools democratize AI app development, unleashing a new wave of innovation that will transform workflows and augment human capabilities across every team and function.”
Trailblazers spearhead the AI revolution: New research shows that IT teams list a “lack of AI skills” as their top challenge when implementing AI. Building on its library of AI learning content, Salesforce is launching new Trailhead courses on Einstein Copilot and Prompt Builder — empowering admins and developers to sharpen their skills with a focus on AI. More than 6 million Trailblazers have used Trailhead to learn, connect, and expand their careers and have earned more than 1 million AI badges since June 2023.
“Developers are taking the reins and steering businesses through the AI revolution. In just a short time, we’ve seen developers build and deploy AI in ways that have transformed nearly every industry,” said Ann Weeby, SVP of Trailhead, Salesforce. “Trailhead’s mission is to empower the innovators of tomorrow by offering free access to the skills and career opportunities that will define the next generation of business and technology.”
Customer perspective:
“We’ve been eager to tap into the power of generative AI in our business, but data privacy and security concerns were a blocker until now with Prompt Builder. It allowed us to safely build generative AI experiences that save our users precious time, while still keeping our data secure and inside of our org.” – Andrew Russo, Salesforce Architect, BACA Systems
“Prompt Builder allows our team at Carnegie Learning to bring our CRM data into our prompts easily with no code! This helps us augment our business processes to cut down on service rep response, email outreach, and content generation time.” – Marissa Scalercio, VP of Sales Operations, Carnegie Learning
Pricing:
Customers can access Einstein 1 Studio by purchasing Einstein 1 Editions or by adding it on to Enterprise or Unlimited Editions. Detailed pricing information is available here.
Global availability:
Prompt Builder and Model Builder are now generally available globally. Copilot Builder is available in beta globally.
Einstein 1 Studio currently supports data residency in the United States and the English language.
Model Builder support for fine-tuning LLMs on Data Cloud data will be available later this year, starting with Amazon Bedrock, Google Vertex AI, and OpenAI LLMs.
