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Snowflake launches new AI platform
Why it matters: The product launch shows how enterprise software companies are aggressively responding to a workplace reshaped by AI. How it works: The new platform, Project SnowWork, essentially provides the "last mile" connecting enterprise data and work systems through AI agents on behalf of employees in sales, finance, operations, HR and other teams. * A user could ask SnowWork to build a pitch deck, and the platform would pull data from multiple sources, organize it, and draft an accompanying email -- no coding needed, CEO Sridhar Ramaswamy tells Axios. * And these "end-to-end" workflows can be automated through SnowWork. Zoom in: Snowflake says it's just starting to offer a limited set of customers a research preview of SnowWork. * It's different than other AI agents that typically function via documents, emails or online content, because it "is grounded in governed enterprise data and context that is embedded directly within the Snowflake platform," the company said in a statement. * "AI models can be very powerful orchestrators of work," Ramaswamy says. Zoom out: Snowflake was among the software companies whose stock prices got ensnared in a selloff earlier this year amid fears that AI could devastate such businesses -- the so-called SaaS-pocalypse.
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Snowflake previews project to automate workflows with AI agents - SiliconANGLE
Snowflake previews project to automate workflows with AI agents Snowflake Inc. today is digging deeper into the emerging agentic enterprise model with the introduction of a research preview of an autonomous artificial intelligence platform designed to help business users automate complex tasks using Snowflake-governed data. The company said the platform, called Project SnowWork, is intended to move AI beyond queries and toward systems that can plan and execute multi-step workflows using enterprise data. While positioned as allowing users to "simply ask for what they need and have SnowWork securely complete the task," the platform works best with existing processes, said Bala Kasiviswanathan, vice president of developer and AI experiences at Snowflake. "Project SnowWork is most powerful when it's working with governed data, defined workflows and an understanding of how the business operates," he said. "Where it really adds value is not just automating tasks, but accelerating decision-making. It can synthesize data, surface insights and recommend next steps." SnowWork runs on governed enterprise data stored on Snowflake's platform and integrates business context, such as metrics, definitions and access policies. Snowflake executives said grounding AI agents in enterprise data is essential if companies want AI to move beyond experimentation and become a trusted operational tool. "The real issue enterprises are facing right now isn't just building agents," Kasiviswanathan said. "It's that most approaches aren't actually solving the business problem fast enough, or in a way that's grounded in real enterprise context." SnowWork orchestrates tasks such as querying datasets, analyzing results, generating reports and preparing presentations within a single interaction. The company said the system can handle workflows that span multiple enterprise systems while observing the same governance and security rules applied to the underlying data. Kasiviswanathan actions taken by the AI agent remain transparent and auditable. "Every action inherits role-based access controls, data policies and audit logging automatically," he said. "That means it can only act on data the user is allowed to see, and every step is fully traceable." The company also emphasized mechanisms it has put in place to reduce the risk of unreliable outputs or hallucinations when the system performs complex tasks. "Enterprises can inspect the steps, validate outputs and maintain control over how and when actions are executed," Kasiviswanathan said. Snowflake positions the new offering as the next stage in a long-running industry effort to democratize access to analytics. Previous waves of "self-service" data tools promised to eliminate the need for specialized data teams, but many organizations still rely heavily on analysts to create reports or interpret dashboards, it noted. Kasiviswanathan said SnowWork aims to go further by completing tasks rather than simply returning answers. "We're collapsing the entire chain from question to analysis to outcome into a single interaction," he said. "Project SnowWork doesn't just surface insights, it carries them through to a finished deliverable or recommended action." Another key point of differentiation is context, he said. "Project SnowWork understands how the business actually operates," he said. "This isn't just democratizing access to data, it's democratizing the ability to act on it." Snowflake didn't say when Project SnowWork will be generally available.
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Snowflake launches autonomous AI platform to automate business workflows
SnowWork is positioned as an extension of Snowflake's AI Data Cloud, and is meant for employees across functions such as finance, sales, and operations. The tasks it assists with range from generating executive-ready reports and forecasting presentations to performing analyses that identify customer churn or operational bottlenecks. Cloud software company Snowflake has launched a new enterprise AI platform, called Project SnowWork, for business users to automate their workflows. The agentic platform is designed to act as an autonomous AI partner that can execute complex business tasks only through conversational prompts. The company has announced the project's research preview this week as part of its broader push into the "agentic enterprise" space. SnowWork is positioned as an extension of Snowflake's AI Data Cloud, and is meant for employees across functions such as finance, sales, and operations. The tasks it assists with range from generating executive-ready reports and forecasting presentations to performing analyses that identify customer churn or operational bottlenecks. The system aims to reduce the manual effort required in coordinating data analysis, reporting, and decision-making processes across business departments. Project SnowWork is built to autonomously plan and execute multi-step workflows tied to data in Snowflake's governed environment. It integrates AI capabilities directly into the enterprise data platform, offering a desktop-based experience for its clients. Users can initiate actions through simple language prompts, with the platform querying data, applying analysis, synthesising insights, and producing structured deliverables. Snowflake has emphasised that the platform operates within the company's existing data governance and security framework. Project SnowWork automatically enforces Snowflake's role-based access controls, masking policies, and audit logging, ensuring compliance and traceability as the AI executes workflows. The company is also offering pre-built, persona-specific AI profiles tailored to functional roles, reducing onboarding time for enterprise users. The launch is part of Snowflake's plan to expand capabilities beyond analytics to execution. For years, enterprises have invested heavily in data and AI technologies, but operationalising insights across teams has remained largely manual. Snowflake is aiming to make Project SnowWork a step toward closing that gap and embedding AI directly into day-to-day operations. Project SnowWork adds to Snowflake's AI product ecosystem, which includes Snowflake Intelligence, a conversational analysis agent for business insights, and Cortex Code, an AI-driven development assistant for engineering and data teams. Over the past few years, the startup has focussed on strengthening its core analytics layer. In an interview with ET, CEO Sridhar Ramaswamy said the company is building out its India team as well. "We've invested significantly in our India operations. We have a 500-plus person team in Pune and offices in Delhi and Bengaluru. Many of our partners are based in India as well -- about half our APJ (Asia Pacific and Japan) partners are here," Ramaswamy said. The company had announced that it will acquire Observe, an AI-powered platform, to deliver observability capabilities to enterprises building AI-driven applications. It has also signed a $200 million deal with artificial intelligence company Anthropic to deepen AI integration across its cloud data platform.
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Snowflake launches desktop AI agent for enterprise workflows - The Korea Times
Christian Kleinerman, executive vice president of product at Snowflake, speaks during the company's media event in Seoul, Thursday. Courtesy of Snowflake U.S.-based software company Snowflake launched Project SnowWork, an artificial intelligence (AI) assistant designed to automate enterprise workflows, in a research preview on Thursday, marking the latest step in its push to bring agentic enterprise AI directly to business users' desktops. "The key insight (of the platform) is we will be introducing 'profiles' ... There is a profile for product managers, sales leaders and finance. And it personalizes every enterprise context to that specific role with the right data, right skills and right insights," Christian Kleinerman, the company's executive vice president of product, said during a media event in Seoul's Jung District. "We are incredibly excited to work with customers to shape what we think is the future of work and the future of the agentic enterprise." Project SnowWork allows business users to request tasks in natural language and have AI autonomously plan and execute multi-step workflows -- from data analysis to report writing and presentation generation. By combining multi-step task execution, persona-specific skills and built-in security and access controls, it is designed to act as a trusted agentic partner that can safely act on enterprise data rather than just summarize it. The launch reflects Snowflake's strategy for a broader enterprise AI stack, which already includes Snowflake Intelligence agent for natural-language analytics and Cortex services for building and deploying customized AI tools. The software company provides a single environment where enterprises can store, process, manage, analyze and share data, and even build applications and AI workloads on top of this data foundation. It currently serves more than 13,300 customers globally. With this new addition, users can move from intent to execution without filing tickets with data teams or waiting on static dashboards, while developers can use tools, such as Cortex Code, to productionize new AI workflows inside the same governed Snowflake environment. "Our goal is to help companies of all sizes, all industries, to make AI real and productive for all users," Kleinerman said. "It is for everyone in the company to leverage all the business logic they have and help them think through structured data, semi-structured data, unstructured data and streaming data." Since launching in 2021, Snowflake Korea has rapidly expanded its footprint, signing up around 80 percent of Korea's top 10 conglomerate groups and growing local platform consumption more than ninefold over the past four years. The company highlighted e-commerce operator Lotte ON, which used Snowflake's AI data platform to break down data silos and power AI-driven use cases such as customer segmentation and real-time product recommendations, delivering a 32-percent reduction in operating costs and a 40-percent improvement in overall performance.
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Snowflake has launched Project SnowWork, an autonomous AI platform designed to automate business workflows through natural language prompts. The system executes multi-step tasks across finance, sales, and operations by pulling from governed enterprise data. Currently in research preview with select customers, the platform addresses enterprise demands for AI that moves beyond analysis to execution.
Snowflake has unveiled Project SnowWork, an enterprise AI platform that allows business users to automate business workflows through conversational prompts rather than coding
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. The system represents a significant shift in how enterprise software companies respond to workplace demands reshaped by AI agents, moving beyond traditional analytics to autonomous execution2
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Source: ET
CEO Sridhar Ramaswamy explains that users can ask Project SnowWork to build a pitch deck, and the AI platform will pull data from multiple sources, organize it, and draft an accompanying email without requiring any coding
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. These end-to-end workflows can be fully automated, marking a departure from systems that merely return answers.The platform is designed to plan and execute multi-step tasks using enterprise data stored within Snowflake's governed environment
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. According to Bala Kasiviswanathan, vice president of developer and AI experiences at Snowflake, the system works best with governed data, defined workflows, and an understanding of how the business operates2
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Source: SiliconANGLE
Project SnowWork orchestrates tasks such as querying datasets, analyzing results, generating reports, and preparing presentations within a single interaction
2
. The system assists employees across finance, sales, and operations with tasks ranging from generating executive-ready reports and forecasting presentations to performing data analysis that identifies customer churn or operational bottlenecks3
.Unlike AI agents that typically function via documents, emails, or online content, Project SnowWork is grounded in governed enterprise data and context embedded directly within the Snowflake platform
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. Every action inherits role-based access controls, data policies, and audit logging automatically, meaning the system can only act on data the user is allowed to see, and every step is fully traceable2
.The company emphasized mechanisms to reduce the risk of unreliable outputs or hallucinations when performing complex tasks
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. Enterprises can inspect the steps, validate outputs, and maintain control over how and when actions are executed, ensuring transparency and auditability remain central to the platform's operation.Christian Kleinerman, executive vice president of product at Snowflake, revealed that the platform introduces persona-specific profiles tailored to roles such as product managers, sales leaders, and finance professionals
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. These profiles personalize enterprise context to specific roles with the right data, skills, and insights, reducing onboarding time for enterprise users3
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Source: Korea Times
Users can initiate actions through natural language prompts, with the platform querying data, applying analysis, synthesizing insights, and producing structured deliverables
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. This approach aims to democratize the ability to act on data, not just access it, collapsing the entire chain from question to analysis to outcome into a single interaction2
.Related Stories
Snowflake is offering a limited set of customers a research preview of Project SnowWork, though the company has not announced when it will be generally available
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. The platform adds to Snowflake's AI product ecosystem, which includes Snowflake Intelligence, a conversational analysis agent for business insights, and Cortex Code, an AI-driven development assistant for engineering and data teams.Positioned as an extension of Snowflake's AI Data Cloud, the launch reflects the company's strategy to expand capabilities beyond analytics to execution
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. Ramaswamy noted that AI models can be very powerful orchestrators of work, addressing enterprise challenges where most approaches aren't solving business problems fast enough or in ways grounded in real enterprise context1
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.The product launch arrives as Snowflake and other enterprise software companies face pressure from AI disruption, with stock prices caught in a selloff earlier this year amid fears of a so-called SaaS-pocalypse
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. The company is simultaneously expanding its global footprint, with Ramaswamy highlighting a 500-plus person team in Pune and offices in Delhi and Bengaluru, with about half of Asia Pacific and Japan partners based in India.Since launching in 2021, Snowflake Korea has signed around 80 percent of Korea's top 10 conglomerate groups, growing local platform consumption more than ninefold over the past four years
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. E-commerce operator Lotte ON used Snowflake's platform to power agentic AI use cases such as customer segmentation and real-time product recommendations, delivering a 32-percent reduction in operating costs and a 40-percent improvement in overall performance4
. The company has also signed a $200 million deal with Anthropic to deepen AI integration across its cloud data platform.Summarized by
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