Snowflake opens Seoul office to boost cross-border data collaboration and AI services
Snowflake has opened a formal office in Seoul, strengthening its presence in South Korea six years after launching locally. At a media briefing held at its Korea headquarters in the POSCO 역삼 Tower in Gangnam, CEO Ki-Young Choi said the company aims to solidify its role as a strategic partner for customers undergoing digital transformation and AI-driven changes.
Snowflake Korea started operations in 2021 and is the fifth Snowflake office in the Asia-Pacific and Japan region. The Korea team numbers about 85 employees and is expected to surpass 100 soon. The newly expanded office includes space for customer training, a technical support team, and a consulting-delivery unit to support partners and clients.
In Korea, roughly 80% of the country’s top 10 conglomerates are Snowflake customers, spanning industries from manufacturing and finance to retail, distribution and entertainment. Globally, Snowflake serves more than 13,300 customers. The company reported fiscal year 2026 revenue of about $4.68 billion, up about 29% from the previous year. Choi attributed the growth to a pricing model that charges customers only for the computing and storage resources they actually use, which supports a wide range of client sizes—from startups to large enterprises.
Im Jin-sik, head of Solution Engineering at Snowflake Korea, outlined the company’s technology vision, noting a shift from generative AI to enterprise “agent AI.” He said Snowflake’s role is to connect data silos across multi-cloud environments and diverse data types and architectures under governance, so that data can be transformed into actionable business outcomes.
A live demonstration showcased Cortex Code, Snowflake’s AI coding agent. The tool can navigate data via natural language, automatically generate and optimize SQL queries, and create applications and agents, accessible through both Snowflake’s SnowSight UI and a command-line interface. In the demo, Cortex Code autonomously generated a skill to collect and summarize Snowflake’s official blog, and users can specify preferred large language models such as Claude for use within the system.
Snowflake Intelligence, the company’s enterprise AI assistant, works by answering questions in natural language while searching both internal structured and unstructured data and external web data to produce insights. Cortex Agents coordinate this workflow, with Cortex Analyst handling structured data searches and Cortex Search handling unstructured data, including optional external data sources. Snowflake emphasizes that, unlike generic chatbots, its platform can leverage customers’ data stored within Snowflake for direct analysis and insight generation.
Industry observers in the United States will note that Snowflake’s Korea expansion reflects broader adoption of AI and data analytics in Asia, aided by American cloud-native platforms. For U.S. companies, the development signals growing opportunities for cross-border data collaboration, supply-chain analytics, and enterprise AI deployments that rely on secure governance of multi-cloud data assets across markets. It also underscores ongoing demand for scalable, consumption-based pricing and agent-style AI tools that can integrate with existing enterprise data ecosystems.