Salesforce Introduces Data Cloud Vector Database

Salesforce today introduced Data Cloud Vector Database to help businesses unify and unlock customer data that is trapped in PDFs, emails, transcripts, and other unstructured formats.

Businesses can now analyze unstructured data sources, like call transcripts, online customer reviews, and support tickets, directly into the customer profile. These enriched profiles then enable teams and AI to search through vast volumes of this data to find insights that can be used to enhance sales, service, marketing, and commerce experiences.

Data Cloud uniquely harnesses Salesforce metadata in the Einstein 1 Platform by linking unstructured and structured data. With this combined data, analysts can now explore and visualize in Tableau, developers can create Salesforce Flow automations, and business users can ground their generative AI prompts. It also reduces the need to fine-tune large language models (LLMs) while improving the accuracy of results provided by Einstein Copilot, Salesforce's conversational AI assistant.

Data Cloud can now ingest disparate unstructured content from customer interactions across multiple touchpoints, including websites, social media platforms, and commerce channels, at scale. It then uses the power of generative AI to create embeddings on unstructured data that are indexed in the vector database. Additionally, businesses can choose to include relevant structured attributes and semantically query the vector database. This enhanced data retrieval capability powers prompts and copilots to deliver more relevant, accurate, and up-to-date responses.

Using Data Cloud Vector Database, customers can improve prospecting, respond quicker to sales proposal requests, personalize outreach and customer engagements, manage knowledge, improve cross-sell and upsell recommendations, and proactively resolve issues.

"For the first time, business users can bring 90 percent of untapped data to their workflows, which has so far remained unstructured and unused in their enterprises. With the new innovation in Data Cloud, businesses can now grow cost-effectively by delivering transformative and integrated customer experiences across service, sales, marketing, AI, automation, and analytics," said Rahul Auradkar, executive vice president and general manager of unified data services and Einstein at Salesforce, in a statement.

In related news, Salesforce today also added other capabilities to get even more value from AI and Data Cloud. They include the following:

• Hybrid search, which improves search accuracy by combining semantic search with traditional keyword search.
• Data Cloud in Sandbox environments, which enables IT teams to configure and test Data Cloud innovations within existing Salesforce Sandboxes before deployment. All of Data Cloud's metadata, including data streams, calculated insights, zero-copy integrations, and search indexes, are available to be customized against existing Salesforce configurations and workflows.
• Salesforce DevOps Center will support Data Cloud, integrating it into the existing application lifecycle management process.