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Four Key Takeaways from TrailblazerDX

Akshay Tdx 3

Last week, I attended TrailblazerDX in San Francisco, where the content was all about Salesforce Data Cloud and AI! There were over 300 sessions to attend, from technical talks to hands-on workshops where attendees could learn how to build copilots and how to use the latest Salesforce platform features directly from product managers, architects, and fellow developers.  

Akshay Tdx

I attended several hands-on sessions, where I learned about new and upcoming product features and talked with numerous people about Data Cloud and AI.  

Here are my key takeaways: 

  1. AI can help boost the sales cycle. Einstein Copilot (GA) is Salesforce’s conversational AI assistant that understands metadata and data permissions, which enable users to interact with it using natural language. It can find or summarize records, draft sales emails, and aggregate data. In Sales Cloud, for example, Einstein Copilot assists the seller from the beginning of the sales cycle, helping convert a lead to a closed won opportunity. 
  2. A vector database and generative AI-powered search are being added to Data Cloud to help bring unstructured data into CRM data. These capabilities are Data Cloud Vector Database and Einstein Copilot Search – see below for additional details regarding Data Cloud Vector Database.  
  3. ApexGuru, a code optimization AI tool, was announced. It has various language code analysis capabilities and can find issues and resolve them without a developer having to spend time reviewing the problem and figuring out how to fix it.  
  4. Slack with Einstein AI. Einstein AI can provide a conversation summary or help find answers for natural prompts. This capability is generally available, but clients must work with their Account Manager to enable an additional SKU. 


What Are Vector Databases?  

Accurate and pertinent generative AI prompts are necessary for the broadest possible set of enterprise data. Up to this point, fine-tuning the model has been costly and labor-intensive. 

Customers can deploy reliable and pertinent generative AI across all Salesforce applications without fine-tuning an off-the-shelf large language model (LLM) thanks to Data Cloud Vector Databases, which have the ability to quickly unify business data into any AI prompt. The Data Cloud Vector Database, integrated into the Einstein 1 Platform, provides AI, automation, and analytics for better decision-making and customer insights across all Salesforce CRM applications.  

By seamlessly utilizing all business data to enhance AI prompts, the Data Cloud Vector Database will eliminate the need for LLM fine-tuning and enable customers to use various data types across their business applications and workflows. By merging structured and unstructured data – such as purchase history, customer support cases, and product inventory – with unstructured data – such as PDFs, emails, documents, and transcripts – boosts business value and ROI across all Salesforce applications.  

Improved AI search capabilities are now included in Einstein Copilot Search. Einstein Copilot Search will respond to and interpret intricate user queries using various data sources, including unstructured data.  

If you missed TDX or want to learn more about any of these topics, catch on-demand sessions on Salesforce+


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Akshay Kumar

Akshay is a technology enthusiast who loves to solve everyday problems and improve existing ones. He thrives at the crossroads of business and technology. In his free time, Akshay works as a Salesforce consultant for a Nonprofit called LBFE. He helps connect volunteers and implement technology for the benefit of the underprivileged in our society. Akshay also mentors other Salesforce enthusiasts through various mentorship programs. He is an avid hiker wanting to explore all the national parks in the United States.

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