en.Wedoany.com Reported - Snowflake unveiled an AI-driven industry customer data integration strategy at the Salesforce annual AI Agent conference "AgentForce World Tour Korea 2026," held at COEX in Seoul, South Korea, aimed at enhancing business outcomes across various industries.
Snowflake CSP Partner Lead, Managing Director Cho Dong-gyu, delivered a keynote titled "Snowflake x Salesforce Real-World Cases: From AI-Based Customer Data Integration to Revenue Growth," explaining how to jointly leverage Snowflake and Salesforce to enable AI Agents to gain insights based on highly reliable data.
Snowflake and Salesforce have collaborated since 2015 across product developments including Tableau, Mulesoft, Data 360, and Agentforce. Tableau allows users to analyze data by directly connecting to Snowflake. Mulesoft facilitates data loading, query execution, and synchronization between Snowflake instances and external business applications.
Data 360 enables secure, zero-copy bidirectional integration, allowing data usage without extraction, transformation, or loading (ETL). Agentforce combines data insights from Snowflake and Salesforce to deliver more personalized experiences. Snowflake noted in its announcement that while many enterprises are expanding AI adoption, customer and operational data remain fragmented across multiple systems, preventing AI from reaching its full potential. Businesses need to enable different members to utilize data across various tools and environments, and establish a foundation for measurable growth, productivity improvements, and differentiated customer experiences.
The core strategy is the zero-copy bidirectional integration between Salesforce Data 360 and the Snowflake AI Data Cloud. This approach connects Salesforce customer touchpoint data with enterprise data stored in Snowflake, allowing AI Agents to leverage richer data insights. Salesforce Data 360 links customer data with actual sales, service, and marketing execution. The Snowflake AI Data Cloud provides the foundation for collecting, storing, and analyzing enterprise-wide data. Connecting both platforms enables secure data utilization without moving or copying data, offering broader insights for AI Agents.
Snowflake also introduced the integration path between Agentforce and Snowflake Agents. Through AI capabilities such as Cortex Agents, Cortex Analyst, and Cortex Search, Snowflake provides an environment for utilizing both structured and unstructured data. These features connect with Agentforce via Snowflake-managed MCP servers. When additional data and insights are needed, Agentforce can communicate with Snowflake MCP servers to retrieve information, and Snowflake users can also leverage Agentforce Agents through MCP clients.
Industry use cases were also presented. In media and sports, fragmented fan data can be integrated to deliver personalized content and enable real-time automated responses. In financial services, customer profiles and AI model results can be directly connected to sales operations for personalized recommendations. In retail and consumer goods, customer data dispersed across brands can be integrated, and advertising effectiveness can be analyzed or predicted via a Data Clean Room without copying or transferring personal information. In healthcare and pharmaceuticals, clinical data and customer data can be connected to support AI-driven decision-making. Snowflake CSP Partner Lead, Managing Director Cho Dong-gyu, stated that for AI Agents to truly deliver business outcomes, a foundation connecting reliable data with customer insights must be established. Based on close collaboration with Salesforce, Snowflake will support South Korean enterprises in securely connecting fragmented data and linking AI Agents to actual business processes, thereby extending to customer experience and business innovation.
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