A：Snowflake's mission is to empower every enterprise to achieve its full potential through data. It intends to achieve this by focusing on the data life cycle with an AI data cloud that enables faster innovation and removing friction from business operations.

A：Snowflake's non GAAP operating margin signifies the company's focus on operational efficiency and growth. The non GAAP operating margin of 11% reflects this commitment to operational rigor across the business, leading to greater efficiency and the ability to invest aggressively in growth.

A：Snowflake's introduction of AI and data integration tools such as Snowflake Intelligence and OpenFlow has enhanced the customer experience by simplifying data management and providing access to actionable insights. This has allowed customers like Booking.com and the Intercontinental Exchange to use the platform for better data access, improved decision-making, and operational efficiency.

A：Snowflake Intelligence is a platform that enables users to interact with enterprise data through natural language, transforming structured, unstructured, and semi-structured data into actionable insights. Early adoption includes customers like Can Health Solutions, which leveraged it to create an intelligent agent for improving health outcomes, and Doctor Creek Technologies, which used it to increase efficiency across finance, sales, and HR in the insurance industry.

A：The advancements in Snowflake's AI capabilities within SQL include the introduction of Cortex AI for SQL, allowing customers to invoke AI models directly within Snowflake. This eliminates data movement and unifies analytics and AI in a single step, contributing to faster and more seamless performance.

A：The introduction of Snowflake's connectivity platform signifies an expanded capability for seamless access to all enterprise data, supporting various formats including structured, unstructured, and streaming data. This platform makes it easier to bring new workloads into Snowflake and supports change data capture from Oracle through a strategic partnership, indicating a broader reach into the $17 billion data integration market.

A：Snowflake is helping its customers with data sharing and collaboration by enabling them to share data effectively across different sources, which drives a powerful network effect that strengthens the ecosystem and expands customer value. As of the quarter, over 1200 accounts are using Open Data Format, underscoring Snowflake's leadership in truly open standards for enterprise data management.

A：Snowflake uses AI-driven automation to speed up large-scale migration, minimize manual recoding, and reduce risk, enabling customers to move faster and with greater confidence.

A：Thompson Reuters is transforming business user access to information by deploying AI-powered agents on Snowflake Cortex, which provides real-time insights, handles drag and text with SQL, and reduces time and cost in functions like finance and HR. BlackRock is using Snowflake AI to serve clients more effectively by pulling together every piece of information on a client from various sources for instant insights.

A：Snowflake is becoming the destination for next-generation applications such as Thermophoretic AI and agentic AI platforms, which automate workflows for tasks like supply chain and regulatory compliance. The company remains committed to efficient scaling by strengthening its platform and introducing new capabilities.

A：Snowflake has more than 12,000 global partners including cloud providers, technology innovators, and system integrators. This partnership ecosystem is enabling the company to deliver value to both existing and new customers quickly and professionally.

A：In Q2, product revenue growth accelerated with a year-over-year increase, new customer adds outperforming expectations, and 50 customers crossing the $1 million in trailing 12-month revenue mark. The company also ended Q2 with strong financials including non-GAAP product gross margin, non-GAAP operating margin, and adjusted free cash flow margin. The operational strategy includes investing strategically for growth and laying groundwork for continued scale.

A：For Q3, Snowflake expects product revenue between $1.125 billion and $1.13 billion, representing 20% year-over-year growth, and a non-GAAP operating margin of 9%. The company has increased its product revenue guidance for FY26 to $4.395 billion, with an expected non-GAAP product gross margin, non-GAAP operating margin of 9%, and non-GAAP adjusted free cash flow margin of 25%.

A：Europe is still developing but is contributing to the new customer momentum. The company is laying the groundwork there, having set up a new motion in the US first, and expecting similar performance from EMEA and Apj as in the US.

A：The acceleration in Snowflake on Azure was mainly due to better alignment between Snowflake's field team and Microsoft, leading to a lot of attention and effort invested in the last six months. Additionally, Microsoft's strength in the EMEA region and the uptick in business with large accounts contributed to the growth.

A：The collaboration with Microsoft contributed to the results through both depth and breadth of partnership. The companies worked closely at an infrastructure level, in products like Office Copilot and RBI, and in go-to-market partnerships. This collaboration is seen as a long-term benefit and is expected to yield more results in the future.

A：The newer products that drove the upside in revenue were incorporated into the guidance for the upcoming quarter based on the modest amount forecasted for them and the consumption patterns seen at the time the forecast was set. The outperformance in Q2 was unexpected but the forecast was based on the current consumption trends.

A：The acceleration in consumption is being driven by the recognition that the AI components of Snowflake's data platform deliver enormous value, leading to budget allocation from large customers for AI projects. The ease of use, governance, and trustworthiness of AI are key factors in customers choosing Snowflake for their AI initiatives.

A：AI is considered an emergent and increasingly powerful force, but the specific timeline for widespread adoption in the enterprise was not clearly defined. The speaker acknowledged that while AI's influence in the consumer world is becoming evident, the transition to the enterprise is not specified, emphasizing that AI is about to work through tangible business cases without a clear indication of when.

A：Supporting Spark on Snowflake is significant because it was a new announcement and indicates expanding capabilities and versatility of the Snowflake platform. Although the details were not elaborated upon in the transcript, the introduction of support for Spark on Snowflake is likely to be a point of interest for users and developers due to the performance and functionality benefits it may offer.

A：Thanks to partnerships with OpenAI, Snowflake intelligence can now perform cross-cutting analysis of popular use cases and trends, and create complex plans, without the need for an analyst. The platform has been enhanced to offer AHA moments to customers by combining the world's best models with their business data.

A：Snowflake has outperformed all other Spark distributions in terms of performance and cost-efficiency, according to customer feedback. The adoption of the familiar set of APIs and programming models from Spark, coupled with Snowflake's performance and cost benefits, has been made possible through the use of Snowpark forSpark.

A：Snowflake's recent revenue beat was driven by strong consumption trends within customers, which is reflected in the net revenue retention and the uptick in new products. The company also experienced a GA (Generally Available) release of new features, which have been a focus area for the engineering and product team over the last 1.5 years.

A：Snowflake has significantly increased its sales and marketing headcount in the first few months of the year, hiring more than in the prior years combined. With a focus on productivity, the company has also added more sales engineers (SES) and specialty sales people. The emphasis is on maintaining high productivity rates among sales reps, and the strategy is anticipated to ramp up as these hires become fully integrated, with the first half of the year expected to see a higher number of hires than the second half.

A：The sequential growth in product revenue and customer adds was primarily driven by large customers migrating new workloads, which contributed to outperformance. Some customers' contributions were also seen in the adoption of Snowflake's acquisition of Postgres, named Crunchy. However, it is the core business that significantly drove the substantial upside in the quarter.

A：Snowflake is recognized as the best AI data platform, widely acknowledged by customers and new prospects. The company excels in ease of use, simplicity, connectedness, and data shareability. The platform also offers a trustworthy environment with comprehensive governance, which are qualities increasingly noticed by customers. While some customers may prefer other platforms for specific features, Snowflake feels confident in its ability to deliver strong analytics and bring new products to the market, such as PostgreSQL OpenFlow and machine learning support. This differentiation contributes to the acceleration in both new customer acquisition and the adoption of AI across existing customers.

A：The increase in professional services revenue indicates that customers are seeking Snowflake for more consultative and strategic deals, especially as they expand into various types of workloads. This growth in professional services suggests a rise in customers' reliance on Snowflake's expertise for complex projects and integrations, acting as a leading indicator of the company's expanding market presence and customer trust in its services.

A：Snowflake views its role in the ecosystem as more of an expert services provider to help other partners perform professional services, rather than doing all the services itself. The goal is for partners to perform these services.

A：The improvement in net revenue retention rate for Snowflake is primarily driven by the migration of large customers to new workloads which caused an uptick in consumption and then normalized after. Snowflake is also focusing on optimizations to prevent customers from misusing the platform.

A：Snowflake is focusing on new workload use cases that involve on-prem migrations and shifts from first-generation cloud infrastructure from S3 or similar services. They have identified a number of these use cases to go into production and believe they are making significant progress.

A：Snowflake's sales team is evolving in its ability to articulate the business value of Snowflake beyond the cost, focusing on the value received by the customer.

A：Approximately 50% of Snowflake's million-dollar plus customers are from the Global 2000.

A：The integration of Snowflake's offerings, particularly focusing on post-SQL and enterprise capabilities, is progressing extremely well and will be in preview in the coming months with very strong customer interest.

A：Snowflake does not see the performance of frontier models as plateaued across all dimensions. They acknowledge remarkable transformations in code quality over the past six months and see potential for integrating enterprise data into these models. Snowflake believes there is ample runway for growth and progress in this area, including in agentic AI and the ability of AI models to use various tools. They consider it still to be very early days for these technologies.

A：The primary applications of AI in enterprises that are expected to create significant value include insurance claims processing, regulatory reporting, anomaly detection, and due diligence tasks, as these areas are in the early stages of utilizing AI models.

A：Snowflake's monetization strategy for its AI products and features includes a deliberate approach that does not necessitate a massive sales effort. They have introduced AI features in a manner that feels natural and easy to use, allowing for quick value realization and adoption without the need for extensive sales engagement.

A：Snowflake ensures its AI capabilities are user-friendly by designing them as a natural extension of data access and by making them easy to implement. A small specialist team supports this strategy, which has led to broad adoption without the need for a large sales team. Snowflake's approach focuses on creating world-class products, achieving broad adoption, demystifying AI, and identifying use cases that provide massive value to customers while driving revenue.

A：The primary use cases for Cortex AI involve bringing together structured and unstructured information in a custom repository to provide a comprehensive view of a customer. Examples include creating a customer 360 view for sales teams to have all relevant customer information in one place, and the use of AI to take actions such as updating records or sending emails, enhancing the utility of the data.

A：Snowflake plans to stay competitive by continuing to innovate in AI and ensuring its migration technology is up-to-date. This strategy will help customers transition legacy systems faster, which is a significant benefit. Additionally, while the company has a strong core business, it acknowledges the need to innovate in both the core business and in response to AI disruptions. Snowflake is focused on delivering long-term success by innovating and benefiting from the migration of legacy systems to the cloud.