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By Harshal Pimpalkhute
At Snowflake, we are committed to providing our customers with industry-leading LLMs. We’re pleased to bring Meta’s latest Llama 4 models to Snowflake Cortex AI!
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By Marketing AI Council
We’ve seen how Snowflake AI tools are transforming outcomes for our customers. From saving 4,000 hours a year on manual email intake to treating more patients in emergency rooms to saving 75% of costs, AI in Snowflake is making a real impact on businesses around the world. That same transformative power is at work within Snowflake, too.
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By Snowflake
For many organizations across industries, the era of experimental AI has given way to the era of practical implementation. Even those companies still testing and evaluating AI solutions are shifting away from the art of the possible to focus more closely on what will soon produce measurable ROI. “It will no longer be enough for your organization to merely use AI to win the approval of company leadership,” says Samuel Lee, Product Marketing Director for Financial Services at Snowflake.
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By Carlos Nai
Data storage has been evolving, from databases to data warehouses and expansive data lakes, with each architecture responding to different business and data needs. Traditional databases excelled at structured data and transactional workloads but struggled with performance at scale as data volumes grew. The data warehouse solved for performance and scale but, much like the databases that preceded it, relied on proprietary formats to build vertically integrated systems.
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By Vinay Sridhar
Despite the best efforts of many ML teams, most models still never make it to production due to disparate tooling, which often leads to fragmented data and ML pipelines and complex infrastructure management. Snowflake has continuously focused on making it easier and faster for customers to bring advanced models into production.
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By Snowflake
Nearly nine out of 10 business leaders say their organizations’ data ecosystems are ready to build and deploy AI, according to a recent survey. But 84% of the IT practitioners surveyed spend at least one hour a day fixing data problems. Seventy percent spend one to four hours a day remediating data issues, while 14% spend more than four hours each day.
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By Florian Delval
As privacy standards continue to evolve, businesses face a dual challenge: to uphold ethical standards for data use while seizing the opportunities offered by data collaboration. Enter data clean rooms: a privacy-enhancing solution that allows organizations to share valuable insights without compromising compliance.* If you're new to data clean rooms, our recent blog post “Data Clean Rooms Explained: What You Need to Know About Privacy-First Collaboration” breaks down the fundamentals.
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By Tony Cyriac
Many financial services companies are experimenting with AI through pilot programs, but several challenges remain for adoption. Key concerns include data security, the accuracy of large language models (LLMs) and the rigorous scrutiny from regulators regarding AI’s role in financial decision-making. Current use cases are largely internal, with some customer-facing chatbot solutions addressing noncritical service inquiries.
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By Julian Forero
Unstructured text is everywhere in business: customer reviews, support tickets, call transcripts, documents. Large language models (LLMs) are transforming how we extract value from this data by running tasks from categorization to summarization and more. While AI has proved that real-time conversations in natural language are possible with LLMs, extracting insights from millions of unstructured data records using these LLMs can be a game changer. This is where batch LLM inference becomes essential.
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By Snowflake
Some 70% of organizations are actively exploring or implementing large language model (LLM) use cases, but fewer than a third of generative AI experiments have made it into production. A common hurdle? The inability to access and leverage the data crucial for running AI applications effectively. Snowflake’s Accelerate 2025 virtual events dive into the challenges and myriad opportunities offered by AI.
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By Snowflake Inc.
Diego Lomanto, Chief Marketing Officer at Writer, joins Snowflake CMO Denise Persson to discuss the current investment frenzy in AI and how to navigate the hype. Learn how understanding the technology cycle can help marketers identify real value and drive wealth creation. Discover Diego's unique career path from developer to CMO and how his background in technology and engineering shapes his approach to marketing. Gain insights into the societal impact of technology and the importance of reshaping and reforming to drive a better standard of living for humanity.
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By Snowflake Inc.
Looking to scale your cybersecurity and threat monitoring using generative AI? Learn how Sophos leverages Snowflake Cortex AI to analyze massive security telemetry datasets. Jason Mullin, Director of Enterprise Data and Analytics at Sophos, shares how his team modernised their security analytics pipeline on the Snowflake Data Cloud. By integrating Cortex AI alongside tools like CoWork and CoCo, Sophos cut security analysis times and enabled AI-driven insights across their organization.
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By Snowflake Inc.
CoCo Desktop - Built Renxu Hu Renxu built the AI feature behind Snowflake’s fastest-growing habit: building entire data workflows at lightning speed. ️
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By Snowflake Inc.
Nicola Tagoe (Line of Business PMM, Snowflake) and Margaux Bouche (Manager, Demand Generation) show how AI changed the way they build campaigns together. They cover the shift from two-week positioning cycles and data scattered across five tools to a shared Snowflake foundation where PMM and Demand Gen now build in real time. Plus their honest take on the 80/20 rule: AI handles the research and structure. The last 20%, brand voice, bold bets, and the judgment that comes from years in the job, stays with the humans.
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By Snowflake Inc.
Discover how Informometry’s Snowflake-native applications streamline data integration, governance, and analytics. With no-code connectivity, replicate enterprise data from platforms like Netsuite and Salesforce directly into Snowflake. Eliminate complex ETL processes and reduce integration costs while keeping data secure.
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By Snowflake Inc.
The September Snow Report is LIVE Three GA launches, AI cost controls, and Expedition 2026 registration is open. What's new Per-User Quotas are GA Set daily or monthly spending limits per user for CoCo, CoWork, Cortex AI Functions, or warehouse compute — and Snowflake blocks access automatically when limits are hit. Deep Research in Snowflake CoWork is GA Multiple agents analyze your structured data, unstructured content, and external context together and deliver a fully cited report with recommendations in minutes.
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By Snowflake Inc.
See how AI agents use Model Context Protocol (MCP) with FME to connect complex enterprise and spatial data to Snowflake. In this episode of Do It Better with Snowflake, Safe Software CEO Don Murray demonstrates how FME extends Snowflake Cortex AI Agents with FME workflows for data integration, transformation, and spatial analysis. See how Snowflake + FME can help you: Connect complex data: including GIS, CAD, 3D, LiDAR, BIM, ERP, and unstructured data.
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By Snowflake Inc.
The August Snow Report is LIVE Two GA launches for CoCo, warehouse tuning that handles itself, and World Tour in 23 cities. What's new CoCo Desktop is GA A native IDE inside your governed Snowflake environment, so it knows your data models and access policies from day one. Up to 2X faster on complex tasks with 51% fewer tokens than third-party assistants. Cloud Agents are GA Run agentic workflows from your browser in Snowsight. Start with a prompt, close your session, and the agent keeps working on Snowflake's managed infrastructure.
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By Snowflake Inc.
The August Snow Report is LIVE Two GA launches for CoCo, warehouse tuning that handles itself, and World Tour in 23 cities. What's new CoCo Desktop is GA A native IDE inside your governed Snowflake environment, so it knows your data models and access policies from day one. Up to 2X faster on complex tasks with 51% fewer tokens than third-party assistants. Cloud Agents are GA Run agentic workflows from your browser in Snowsight. Start with a prompt, close your session, and the agent keeps working on Snowflake's managed infrastructure.
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By Snowflake Inc.
Assaf Henkin, Co-Founder and CEO of Jedify, joins the Snowflake Summit 2026 News Desk to discuss how enterprises can build AI applications that truly understand their business context. Drawing from 15 years of experience building open source intelligence platforms, Henkin shares insights on balancing innovation with operations, staying true to founding principles while adapting to market changes, and how Snowflake's AI Data Cloud is enabling Jedify to reach new heights in the agentic AI era. Learn what's driving enterprise AI adoption and what founders should focus on for the back half of 2026.
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By Snowflake
There's never been a better time to be an entrepreneur looking for investment funding. Global venture capital activity grew mightily in the first half of 2021, and the trend appears to be continuing as we head into 2022. However, that doesn't mean building a new company is any easier. The same inherent resource and growth challenges exist, and venture capitalists still want to see value creation and strong indicators for future success before they invest.
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By Snowflake
Data scientists require massive amounts of data to build and train machine learning models. In the age of AI, fast and accurate access to data has become an important competitive differentiator, yet data management is commonly recognized as the most time-consuming aspect of the process. This white paper will help you identify the data requirements driving today's data science and ML initiatives and explain how you can satisfy those requirements with a cloud data platform that supports industry-leading tools.
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By Snowflake
Many organizations struggle to share data internally across departments and externally with partners, vendors, suppliers, and customers. They use manual methods such as emailing spreadsheets or executing batch processes that require extracting, copying, moving, and reloading data. These methods are notorious for their lack of stability and security, and most importantly, for the fact that by the time data is ready for consumption, it has often become stale.
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By Snowflake
Most companies that build software have a strong DevOps culture and a mature tool chain in place to enable it. But for developers that need to embed a data platform into their applications to support data workloads, challenges emerge. DevOps for databases is much more complex than DevOps for code because database contain valuable data, while code is stateless. Instantly creating any number of isolated environments Reducing schema change frequency with variant data type
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By Snowflake
DELIVER ALL YOUR DATA WORKLOADS WITH SNOWFLAKE Gartner predicts that 75% of all databases will be deployed or migrated to a cloud platform by 2022. But how does e a cloud data platform enable a long-term strategy for maximizing all of an organization's data assets? Snowflake's cloud data platform is a highly extensible, multi-region and multi-cloud platform that powers all types of data workloads. Specifically, Snowflake: To learn everything Snowflake offers today's, forward-looking organizations, download our white paper, Snowflake: One Cloud Data Platform for All Your Analytic Needs.
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By Snowflake
Companies are moving workloads to the cloud as they seek to improve speed, scale, and agility. Today's data warehouse managers want to boost analytics productivity, increase the ability to scale instantly, and ingest and support a diverse set of data without bottleneck delays. In this white paper, we explain how Snowflake delivers the speed, scale, and agility organizations need for data-driven decision-making.
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By Snowflake
Financial institutions are embracing cloud-based data technologies to improve their service and product offerings, streamline operations, and gain deeper customer insights. This ebook features success stories about the many ways financial services companies are leveraging Snowflake Cloud Data Platform to build a 360 degree view of customers, accelerate financial analysis with unlimited scale, and keep sensitive and regulated data secure.
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By Snowflake
As companies have recognized the importance of unifying customer data to obtain business insights, customer data platforms that consolidate and activate known customer information have become ubiquitous. Customer data platforms enable marketers to segment and share customer profiles with marketing systems to personalize the content of email campaigns, digital ads, and other channels. In this ebook, we explore how marketers can launch and operate a customer data platform successfully, with a focus on how to.
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Snowflake’s mission is to enable every organization to be data-driven. Our cloud-built data platform makes that possible by delivering instant elasticity, secure data sharing and per-second pricing, across multiple clouds. Snowflake combines the power of data warehousing, the flexibility of big data platforms and the elasticity of the cloud at a fraction of the cost of traditional solutions.
Conventional data platforms and big data solutions struggle to deliver on their fundamental purpose: to enable any user to work with any data, without limits on scale, performance or flexibility. Whether you’re a data analyst, data scientist, data engineer, or any other business or technology professional, you’ll get more from your data with Snowflake.
What Makes Snowflake Unique:
- A Multi-Cluster Shared Data Architecture Across Any Cloud: Easily scale up and down any amount of computing power for any number of workloads or users and across any combination of clouds, while accessing the same, single copy of your data but only paying for the resources you use thanks to Snowflake’s per-second pricing.
- Secure Data Sharing and Collaboration: Eliminate the cost and headache of static data sharing methods by easily sharing any amount of live structured and semi-structured data, without having to move data, whether it be across your enterprise, with customers and business partners, or to monetize your data.
- One, Near-Zero Maintenance Platform Delivered as a Service: Choose any combination of infrastructure providers, enable your workloads where you want, rely on Snowflake to manage the data platform, and deploy across and between different clouds and regions to support business efficiencies and data sovereignty.
A Modern Data Platform Built For Any Cloud.