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New Salesforce Vector Database for Data Cloud integrates structured data with unstructured data—case files, call transcripts, Slack, emails, PDFs, audio, and video. This synergy powers the most accurate AI results, advanced automations, and profound customer insights, enabling seamless collaboration between AI and human workers to supercharge your sales, service,...

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Marc Benioff

2,478,907 subscribers

57,889 次观看 • 1 年前 •via X (Twitter)

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Andrew Russo1 年前

@salesforce How can we get emails from our sales teams inboxes into data cloud?

Simon Severino | The Sales Booster 的头像
Simon Severino | The Sales Booster1 年前

@salesforce Proud shareholder. Keep rolling!

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Stephen Mahoney1 年前

@salesforce

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🚀 Introducing Salesforce's game-changer: Data Cloud Vector Database + Einstein Copilot Semantic Search! ✨ Harness both structured & unstructured data for smarter AI responses. No more costly training! Real-time data-driven insights with RAG, complete with citations to curb AI hallucinations. Trust in enterprise AI just got a major upgrade, thanks to Salesforce! ❤️
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🚀 Introducing Salesforce's game-changer: Data Cloud Vector Database + Einstein Copilot Semantic Search! ✨ Harness both structured & unstructured data for smarter AI responses. No more costly training! Real-time data-driven insights with RAG, complete with citations to curb AI hallucinations. Trust in enterprise AI just got a major upgrade, thanks to Salesforce! ❤️

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Unlike Microsoft Copilot, Salesforce Agentforce’s Large Action Models (LAMs) leverage both structured and unstructured data across Salesforce’s secure, scalable ecosystem—Data Cloud, Customer 360, Tableau, Flow, & Slack—to drive real-time, intelligent, autonomous actions. It’s not just automation; it’s AI agents acting with precision, context, accuracy, and compliance, turning routine tasks into autonomous, value-driven actions. Agentforce enables teams to focus on strategy while Autonomous Agents handles the customer and employee workloads, all within a trusted framework that adapts and learns. This is the future of work, powered by Salesforce. This is what AI was meant to be. #Agentforce
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Unlike Microsoft Copilot, Salesforce Agentforce’s Large Action Models (LAMs) leverage both structured and unstructured data across Salesforce’s secure, scalable ecosystem—Data Cloud, Customer 360, Tableau, Flow, & Slack—to drive real-time, intelligent, autonomous actions. It’s not just automation; it’s AI agents acting with precision, context, accuracy, and compliance, turning routine tasks into autonomous, value-driven actions. Agentforce enables teams to focus on strategy while Autonomous Agents handles the customer and employee workloads, all within a trusted framework that adapts and learns. This is the future of work, powered by Salesforce. This is what AI was meant to be. #Agentforce

Marc Benioff

54,097 次观看 • 1 年前

Today, Box announced new AI Agents to work with enterprise content, powering Deep Research, Search, and enhanced Data Extraction. There’s a tremendous amount of value that’s trapped in unstructured data, from contracts to research data, that we can finally unlock with AI.
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Today, Box announced new AI Agents to work with enterprise content, powering Deep Research, Search, and enhanced Data Extraction. There’s a tremendous amount of value that’s trapped in unstructured data, from contracts to research data, that we can finally unlock with AI.

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Today we announced the new Einstein Copilot Search and Salesforce Vector Database in Data Cloud to power semantic search and retrieval augmented generation. This will enhance Einstein Copilot's ability to understand, generate outputs, and automate actions across a wide variety of use cases, contexts, and data/content types. LLMs can't be relied on to recall specific data they were trained on, so the way to make them work in the enterprise, where accuracy is paramount, is to feed them with the right data using hybrid keyword and vector search-powered RAG. By bringing all this seamlessly into our apps and Einstein Copilot UX as well as Hyperforce cloud infrastructure, we can offer high performance, low latency, addressing data privacy, security, and residency requirements🌟
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Sharing our latest short course: Building and Evaluating Data Agents, created in collaboration with Snowflake and taught by Anupam Datta (Anupam Datta) and Josh Reini (Josh Reini). A data agent extracts data from sources such as files or databases, analyzes it, and provides insights and visualizes its findings. But most data agents struggle with reliability or can't handle multi-step reasoning. In this course, you'll learn to build, trace, and evaluate a multi-agent workflow that plans tasks, pulls context from structured and unstructured data, performs web search, and summarizes or visualizes the final results. Learn more and enroll for free!
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Sharing our latest short course: Building and Evaluating Data Agents, created in collaboration with Snowflake and taught by Anupam Datta (Anupam Datta) and Josh Reini (Josh Reini). A data agent extracts data from sources such as files or databases, analyzes it, and provides insights and visualizes its findings. But most data agents struggle with reliability or can't handle multi-step reasoning. In this course, you'll learn to build, trace, and evaluate a multi-agent workflow that plans tasks, pulls context from structured and unstructured data, performs web search, and summarizes or visualizes the final results. Learn more and enroll for free!

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