Salesforce has announced a groundbreaking update to its Einstein 1 Platform with the introduction of the Data Cloud Vector Database and Einstein Copilot Search. These innovations aim to unify business data and enhance AI capabilities across all Salesforce applications, promising significant improvements in productivity and customer experience.

Key Takeaways

• The Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data to enable grounding of AI prompts and Einstein Copilot, eliminating the need for costly and complex fine-tuning of LLM models.
• Built into the Einstein 1 Platform, the Data Cloud Vector Database will enable all business applications to harness the power of unstructured data through workflows, analytics, and automation.
• Einstein Copilot Search will provide AI search capabilities to deliver precise answers from Data Cloud instantly in a conversational AI experience, boosting productivity for all business users.

Enhancing AI with Unified Data

The Data Cloud Vector Database is designed to address the challenge of integrating unstructured data into AI models without the need for expensive and labor-intensive fine-tuning. By unifying various data types, including PDFs, emails, documents, and transcripts, with structured data like purchase history and customer support cases, the database will enrich AI prompts and enhance decision-making and customer insights across all Salesforce CRM applications.

For instance, customer service leaders can improve efficiency and customer satisfaction by using the platform to present relevant knowledge articles to service agents as soon as a case is created. This allows for quick identification of similar cases and the integration of automation, reducing case resolution time and improving the overall customer experience.

Introducing Einstein Copilot Search

Einstein Copilot Search, available in February, will enhance the existing Einstein Copilot by providing advanced AI search capabilities. This feature will interpret and respond to complex queries by accessing diverse data sources, including unstructured data. It will benefit sales, customer service, marketing, commerce, and IT teams by offering an AI assistant capable of solving problems and generating content using real-time business data.

In customer service, Einstein Copilot Search will link a customer’s concerns from unstructured emails and phone call transcripts to their structured support ticket history. This provides service representatives with a detailed understanding of customer issues and AI-generated, data-backed resolution suggestions, enhancing confidence in the AI-generated insights.

The Importance of Data in AI Innovation

Data is crucial for delivering accurate, compelling customer experiences and driving AI innovation. However, 90% of enterprise data exists in unstructured formats, making it largely inaccessible for business applications and AI models. Forrester predicts that the volume of unstructured data managed by enterprises will double by 2024, highlighting the urgency of this challenge. While 80% of IT leaders acknowledge the transformative potential of generative AI, 59% still need a unified data strategy to harness this power.

Use Cases and Benefits

• Customer Service: Customers can receive better, more automated service. For example, a self-service chatbot powered by Einstein Copilot can answer upgrade eligibility questions by pulling relevant details from multiple knowledge sources and citing specific articles.
• Marketing: Marketers can tailor campaigns based on consumer intent and behavior by analyzing unstructured survey data and transcripts in Data Cloud, then iterating on email templates and copy directly from within Einstein Copilot.
• Sales: Sales teams can increase revenue by surfacing insights from prior customer interactions. For instance, a sales rep can use Einstein Copilot to reference specific unstructured data, like a customer’s 10-K or past email interactions, to prepare for meetings with valuable insights.
• IT: IT teams can discover problems and anomalies in product telemetry by ingesting unstructured content from machine operations into Data Cloud. Tableau can then analyze this data, and Einstein can identify and flag unusual data points that reveal equipment problems.

Availability

• Data Cloud Vector Database will be in pilot in February 2024.
• Einstein Copilot Search will be in pilot in February 2024.
• Einstein Copilot will be generally available in February 2024.

Salesforce continues to lead the way in AI and CRM innovation, empowering companies to connect with their customers in new and meaningful ways through the power of unified data and advanced AI capabilities.

Sources

• New Vector Database in Salesforce Data Cloud Will Power AI, Analytics, and Automation Using LLMs with Business Data for Use Across the Einstein 1 Platform - Salesforce, Salesforce.
• New Vector Database in Salesforce Data Cloud Will Power AI, Analytics, and Automation Using LLMs with Business Data for Use Across the Einstein 1 Platform - Salesforce, Salesforce.