SNOW
T2Snowflake Inc.
OverviewSnowflake Inc. offers a cloud-based data platform, the Data Cloud, for enterprises to consolidate data, gain insights, build applications, and securely share in
Snowflake Inc. offers a cloud-based data platform, the Data Cloud, for enterprises to consolidate data, gain insights, build applications, and securely share information. Its consumption-based model drives revenue, with product revenue growing 34% in Q1 FY27. Snowflake is rapidly evolving into an AI-orchestration platform, with over 13,600 accounts leveraging AI capabilities, and recently acquired Natoma.
- What They Do (Plain English & Analogies)
- Snowflake provides a cloud-based data platform that acts like a central, secure digital brain for businesses. Imagine a company's entire collection of information – from sales figures and customer interactions to data from factory sensors – all stored, cleaned, and organized in one accessible place in the cloud. This 'Data Cloud' allows businesses to easily get meaningful insights, build applications that use this data, and securely share it with partners. More recently, Snowflake has added 'super-librarians' or AI agents, like Snowflake Intelligence and Cortex Code (CoCo). These AI tools don't just help find information; they can understand complex business questions asked in plain language, provide answers, and even automate tasks. For example, an AI agent could tell a business which customers are likely to leave next quarter or how a supply chain issue impacted inventory. Customers pay based on how much data they store and the 'compute power' (like electricity) they use to process and analyze it, making it a utility-like service for data and AI.
- Very Brief History
- Founded in 2012 by former Oracle engineers, Snowflake was designed from the ground up for the cloud, separating data storage from processing for greater efficiency. It launched publicly in 2020 with a significant IPO. In February 2024, Sridhar Ramaswamy became CEO, accelerating the company's shift from a traditional data warehouse to an 'AI Data Cloud' focusing on generative AI and autonomous agents. Recent acquisitions include Neeva (2023) for search, Crunchy Data (2025) for PostgreSQL services, Observe (January 2026) for AI-powered observability, and the intended acquisition of Natoma (announced Q1 FY27) to extend its agentic control plane into everyday applications.
- "Street Stereotype"
- Snowflake is often perceived by investors and analysts as the 'Gold Standard' of cloud data platforms, but with a reputation for a 'premium price tag'. The market views it as a high-conviction consumption play, meaning its revenue can be volatile, growing significantly during periods of strong economic activity and innovation, but potentially facing headwinds when companies focus on cost-cutting. Analysts are currently focused on Snowflake's ability to successfully transition into the primary platform for the 'Agentic AI' era, competing against hyperscalers and other data platforms, and demonstrating sustained, AI-driven consumption growth.
- Subsidiaries On Linked In*
- Observe — Acquired January 2026; LinkedIn: observeinc
- Natoma, Inc. — Intended acquisition announced Q1 FY27; LinkedIn: natoma-inc
- Crunchy Data — Acquired 2025; LinkedIn: crunchy-data
- Neeva — Acquired 2023, now part of Snowflake; LinkedIn: neeva-inc
- Customer Sectors & Example Clients
- Snowflake serves a wide range of organizations across various industries, including Financial Services, Technology, Retail, and Healthcare. Specific clients mentioned include Holiday Inn Club Vacations (a leading vacation ownership company), Health (an AI-driven platform for construction and design), one of the largest banks in the United States, Nestle (a global consumer goods company), Global Payments, Depository Trust and Clearing Corporation (DTCC), Blue Yonder, Providence (one of the largest health systems in the United States), and Thomson Reuters (a global provider of legal, tax, and regulatory intelligence).
- New Customers / Segments They'Re Targeting
- Snowflake is actively targeting organizations aiming to become 'agentic enterprises,' where employees and intelligent AI agents work together to accelerate decisions and automate workflows. This involves expanding beyond traditional data warehousing to enable customers to build and run AI-native applications and workflows directly on the platform. Key new segments include the IT operations market through the Observe acquisition, focusing on AI-powered observability, and transactional applications with the general availability of Snowflake Postgres. The intended acquisition of Natoma aims to extend Snowflake's 'agentic control plane' into everyday business applications, allowing users to perform actions like sending emails or managing tasks directly from within Snowflake Intelligence or CoCo.
- Supply Chain And Sourcing Geographies
- As a cloud-based data platform, Snowflake's 'supply chain' primarily involves leveraging the infrastructure of major cloud service providers. The company has a significant reliance on Amazon Web Services (AWS), as evidenced by a $6 billion multiyear agreement to accelerate enterprise AI adoption globally, utilizing AWS's Graviton compute and AI services. Snowflake also operates on other hyperscaler platforms like Microsoft Azure and Google Cloud Platform. Therefore, its sourcing geographies for compute and storage infrastructure are the global data center regions operated by these major cloud providers. Specific country, region, or city details for these data centers are not explicitly disclosed in the provided information, but the operations are global.
- Sales Geographies And Expansion Plans
- Snowflake currently sells its products in the United States and internationally. The company reported strong sales execution across 'all geographies' in the most recent quarter. An expanded collaboration with AWS, involving a $6 billion multiyear agreement, aims to 'accelerate enterprise AI adoption globally.' While there are no specific new geographic expansion plans explicitly disclosed beyond its existing global reach, the focus is on deepening penetration and accelerating AI adoption within its current international markets.
- How Key Themes May Help/Hurt
- The buildout of 'AI '25: Phase 2 Deployment' and 'AI '25: Cloud Platform & Software' themes significantly helps Snowflake. The acceleration of task-specific AI agents and the shift to production-level AI deployment (Bull3 of Phase 2 Deployment) directly aligns with Snowflake's focus on Snowflake Intelligence and Cortex Code, which enable customers to build and run AI-native applications and workflows. Its emphasis on robust governance, security, and auditability for AI agents (Bull2 of Phase 2 Deployment, Bull1 of Cloud Platform & Software) is a key differentiator, as enterprises demand trustworthy AI solutions. The acquisition of Observe for AI-powered observability also aligns with the critical need for mission-critical observability platforms (Bull2 of Phase 2 Deployment). The need for a single, governed data foundation for AI is a strong driver for Snowflake's core platform. However, the themes could hurt if 'ROI anxiety' (Bear1 of Phase 2 Deployment, Bear1 of Cloud Platform & Software) leads customers to throttle AI spend, impacting Snowflake's consumption-based revenue. The commoditization of open-source AI deployment tools (Bear2 of Phase 2 Deployment, Bear2 of Cloud Platform & Software) could put pressure on Snowflake's proprietary offerings if it cannot consistently prove superior differentiation and value. While Snowflake positions itself as a solution to 'escalating security and governance risks' (Bear3 of Phase 2 Deployment), managing these complex risks remains an ongoing challenge.
3 Main Long-Term Bull Details
- Accelerating AI Monetization and Adoption: Snowflake is successfully monetizing AI, with products like Snowflake Intelligence and Cortex Code (CoCo) driving rapid customer adoption (over 7,100 accounts using CoCo, accounts using Snowflake Intelligence more than doubled quarter-over-quarter). This indicates a strong shift from AI pilots to production-level consumption, with AI influencing a substantial portion of new bookings and accelerating the entire data life cycle.
- Strong Enterprise Commitment and RPO Growth: The company continues to secure large, multi-year contracts, evidenced by Remaining Performance Obligations (RPO) growing 38% year-over-year. In Q1 FY27, 8 customers surpassed $10 million in trailing 12-month revenue, bringing the total to 64 customers spending over $10 million, and 46 customers crossed the $1 million threshold in Q1, demonstrating deep trust from large enterprises in Snowflake's long-term data and AI strategy.
- Expanding Platform Capabilities and Ecosystem: Snowflake is continuously innovating, launching over 20% more product capabilities in Q1 FY27 than a year ago. This includes the general availability of Snowflake Postgres for transactional applications, the acquisition of Observe for AI-powered observability, and the intended acquisition of Natoma to extend the 'agentic control plane' into everyday applications. Strategic partnerships with AWS (a new $6 billion multiyear agreement), OpenAI ($200 million partnership), and SAP further expand its ecosystem and make the platform indispensable for diverse AI initiatives.
3 Main Long-Term Bear Details
- Consumption Volatility: As a consumption-based business, Snowflake's revenue remains sensitive to unpredictable customer usage patterns and macro-driven optimizations. While AI workloads are growing, the 'lumpy' nature of large migrations and potential budget tightening can lead to variability in product revenue and make forecasting challenging.
- Intense Hyperscaler Competition and Bundling: Snowflake faces fierce competition from hyperscalers (AWS, Azure, GCP) who are increasingly bundling their own AI and data tools, potentially at lower costs. The risk is that these large platforms could commoditize parts of the data stack, turning 'best of breed' solutions into 'nice to have' if Snowflake cannot consistently prove superior differentiation and value.
- Margin Pressure from AI Investments: While Snowflake is demonstrating operational efficiency, significant investments in AI infrastructure, R&D for agentic AI tools (which have a lower gross margin than the core platform), and acquisitions (like Observe and Natoma) could pressure short-term profitability. The Observe acquisition alone introduces an approximate 150 basis point headwind to the FY27 non-GAAP adjusted free cash flow margin.
- Competitors And Differentiation
- Snowflake competes with major hyperscalers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), which offer their own integrated AI and data tools. It also competes with other data platforms, including legacy data warehouses like Teradata (from which customers are migrating) and modern data platforms like Databricks. Snowflake differentiates itself through several key aspects: it provides a unified, governed data foundation; offers access to leading AI models (through partnerships with Anthropic and OpenAI, and its own Model Garden); ensures secure connectivity across enterprise applications and workflows; and offers a unifying 'agentic control plane' through products like Snowflake Intelligence and Cortex Code (CoCo). Snowflake emphasizes customer choice, independence from the specific mechanics of individual cloud providers (operating across AWS, Azure, etc.), and model choice. Its core competitive advantage lies in its enterprise-grade governance, security, and auditability, which are crucial for trusted AI deployment.
- Recent Performance & What The Market'S Focused On
- Snowflake reported strong Q1 FY27 results, with product revenue accelerating to 34% year-over-year, reaching $1.334 billion, marking its strongest sequential dollar growth in company history. Net revenue retention increased to 126%, and non-GAAP operating margin expanded over 300 basis points year-over-year to 12%. The company raised its FY27 product revenue outlook from 27% to 31% year-over-year growth, citing strength in its core data platform and a meaningful uplift from AI capabilities like CoCo and Snowflake Intelligence. The market is focused on the accelerating adoption and monetization of AI products, particularly Cortex Code (CoCo), which is driving increased consumption of the core data platform. Investors are also tracking the company's ability to maintain margin expansion despite investments in AI and acquisitions, and the impact of its strategic partnerships and new product capabilities on sustained growth.
- Revenue Segments And Estimated Mix
- Product Revenue — Mix: 100%; Source: Q1 FY27 earnings call, Ticker_DetailedOverview; Trend: Grew 34% year-over-year in Q1 FY27, accelerating from 30% last quarter and 26% a year ago. AI capabilities, including CoCo and Snowflake Intelligence, are providing a meaningful uplift and are a significant revenue engine.
- Product Brands
- Data Cloud
- Snowflake Intelligence
- Cortex Code (CoCo)
- Snowflake OpenFlow
- Snowflake Postgres
- Observe
- Natoma
- Model Garden
- Cortex Analysts
- Cortex Search
Bull / Bear DetailsAs of June 3, 2026, Snowflake is rapidly emerging as the essential agentic control plane for enterprise AI. Accelerated product revenue growth to 34% and a rais
Thesis
As of June 3, 2026, Snowflake is rapidly emerging as the essential agentic control plane for enterprise AI. Accelerated product revenue growth to 34% and a raised FY27 outlook to 31% underscore strong demand, driven by the fastest adoption of AI products like Snowflake Intelligence and Cortex Code. With expanding capabilities via Natoma and strategic cloud partnerships, Snowflake's deep data gravity and consumption model solidify its critical foundation for secure, governed AI deployment, despite inherent usage variability.
Bull case
Snowflake is experiencing accelerating and widespread adoption of its AI products, demonstrating strong monetization. Snowflake Intelligence accounts more than doubled quarter-over-quarter, and Cortex Code is now used by over 7,100 accounts, contributing meaningful AI revenue. This rapid adoption signifies a significant shift to production-level AI deployment, driving incremental core platform consumption and validating Snowflake's AI strategy.
Snowflake demonstrates robust customer momentum and commitment, evidenced by product revenue growth accelerating to 34% year-over-year and net revenue retention increasing to 126%. The company added 616 net new customers, up 38% year-over-year, and now has 64 customers spending over $10 million annually. This underscores strong platform stickiness and expanding enterprise adoption.
Snowflake is significantly expanding its platform capabilities and market opportunity, positioning itself as the agentic control plane. The intended acquisition of Natoma will extend AI governance into everyday applications. New strategic partnerships, including a $6 billion multiyear agreement with AWS and a $200 million partnership with OpenAI, further enhance model choice and integration, making Snowflake indispensable for diverse enterprise AI workloads.
Bear case
While product revenue growth has accelerated and FY27 guidance was raised, Snowflake's consumption-based model still carries inherent volatility. Customer usage patterns and macro-driven optimizations can lead to unpredictable revenue fluctuations, making long-term forecasting challenging despite strong current performance. The risk of future deceleration remains a concern for investors.
The initial gross margin profile of new AI products is lower than Snowflake's core platform, and the Observe acquisition continues to introduce an approximate 150 basis point headwind to the FY27 non-GAAP operating and free cash flow margins. While management aims to offset these with efficiencies, heavy investments in new AI capabilities and strategic acquisitions could pressure overall profitability in the short term.
Snowflake faces intense competitive pressure from hyperscalers bundling their own AI and data tools. Additionally, the risk of "sticker shock" persists as AI agents proliferate on its consumption-based platform. While Snowflake is implementing cost governance features like account-level limits, the potential for unexpected costs could still deter some customers from fully scaling AI agent deployments, impacting adoption rates.
Bull / Bear Case
- Bear Case
- Despite accelerated product revenue growth and a raised FY27 guidance, Snowflake's consumption-based model carries inherent volatility. Customer usage patterns and macro-driven optimizations can lead to unpredictable revenue fluctuations, making long-term forecasting challenging. The initial gross margin profile of new AI products is lower than Snowflake's core platform, and the Observe acquisition continues to introduce an approximate 150 basis point headwind to the FY27 non-GAAP operating and free cash flow margins. While management aims to offset these with efficiencies, heavy investments in new AI capabilities and strategic acquisitions could pressure overall profitability in the short term. Snowflake also faces intense competitive pressure from hyperscalers bundling their own AI and data tools. Additionally, the risk of 'sticker shock' persists as AI agents proliferate on its consumption-based platform, potentially deterring some customers from fully scaling AI agent deployments despite implemented cost governance features.
- Bull Case
- Snowflake is experiencing accelerating and widespread adoption of its AI products, with Snowflake Intelligence accounts more than doubling quarter-over-quarter and Cortex Code (CoCo) now used by over 7,100 accounts, contributing meaningful AI revenue and driving core platform consumption. This rapid adoption validates Snowflake's AI strategy and signifies a significant shift to production-level AI deployment. The company demonstrates robust customer momentum, evidenced by product revenue growth accelerating to 34% year-over-year and net revenue retention increasing to 126%. Snowflake added 616 net new customers, up 38% year-over-year, and now boasts 64 customers spending over $10 million annually, underscoring strong platform stickiness and expanding enterprise adoption. Furthermore, Snowflake is significantly expanding its platform capabilities and market opportunity, positioning itself as the agentic control plane through the intended acquisition of Natoma and strategic partnerships with AWS ($6 billion multiyear agreement) and OpenAI ($200 million partnership), enhancing model choice and integration for diverse enterprise AI workloads.
- More Compelling & Why
- Bear. Given the current valuation, particularly the elevated EV/FCF multiple of approximately 58x-62x for current/forward estimates, the bear case is more compelling. This valuation prices in an aggressive growth trajectory and flawless execution of the AI strategy, leaving little margin for error against consumption volatility and intense hyperscaler competition. The strongest argument for the bear case is that the market has already heavily rewarded the strong Q1 results and AI narrative, pushing the stock to a premium that may not be sustainable if growth decelerates or competitive pressures intensify. My view would flip to bullish if Snowflake demonstrates sustained product revenue growth significantly above its raised FY27 guidance of 31%, coupled with a clear and accelerating path to GAAP profitability, which would justify the current premium valuation.
Key Factors
| Key Factor | Why It Matters | What To Watch | What It Signals | Where/How To Track | Free Alt Data | Paid Alt Data |
|---|---|---|---|---|---|---|
| Rapid Adoption of Cortex Code (CoCo) and Snowflake Intelligence | The rapid adoption of AI products like CoCo and Snowflake Intelligence validates Snowflake's AI strategy and its ability to monetize these new capabilities, driving incremental consumption and expanding the total addressable market. | Total accounts using Cortex Code (currently >7,100) and Snowflake Intelligence (more than doubled quarter-over-quarter, implying >5,000 from 2,500+) in Q2 FY27. | Cortex Code accounts exceeding 8,500 or Snowflake Intelligence accounts exceeding 6,500 in Q2 FY27 = Bullish. | Company earnings press releases and conference calls. Investor presentations. | Google Trends: 'Snowflake Cortex Code' or 'Snowflake Intelligence' search volume. Reddit/MLOps discussions on Snowflake AI adoption. | Thinknum: Job postings mentioning 'Snowflake Cortex' or 'Snowflake Intelligence' for customer roles. |
| Non-GAAP Operating Margin Expansion and Raised FY27 Guidance | Expanding operating margins demonstrate Snowflake's ability to achieve greater efficiency and profitability as it scales, balancing growth investments with disciplined cost management, which is critical for long-term shareholder value. | Q2 FY27 non-GAAP operating margin actuals relative to 12.5% guidance, and any further updates to the full FY27 non-GAAP operating margin guidance of 13.5%. | Q2 FY27 non-GAAP operating margin exceeding 12.5% or an upward revision of FY27 guidance = Bullish. Q2 FY27 non-GAAP operating margin below 12.5% or a downward revision of FY27 guidance = Bearish. | Company earnings press releases and conference calls. SEC filings (Form 10-Q). | Financial news analysis of earnings reports. | Bloomberg Terminal: SNOW margin estimates, consensus changes. |
| Net Revenue Retention (NRR) Rate | NRR indicates the expansion of existing customer spend, reflecting the stickiness of the platform and the success of cross-selling and upselling new features, particularly AI capabilities, which is crucial for a consumption model. | The reported Net Revenue Retention rate in Q2 FY27 (Q1 FY27 was 126%). | NRR stabilizing at 126% or increasing above 126% in Q2 FY27 = Bullish. NRR decelerating below 125% = Bearish. | Company earnings press releases and conference calls. SEC filings (Form 10-Q). | Industry reports on cloud data platform spending trends. | IDC/Gartner: Enterprise spending surveys on data and AI platforms. |
| Growth in Customers Spending >$1 Million and >$10 Million TTM Revenue | An increasing number of large customers signifies deeper enterprise adoption and commitment, indicating successful land-and-expand strategies and the platform's ability to handle mission-critical, high-value workloads, which drives future RPO. | Number of customers spending >$1 million (currently 79) and >$10 million (currently 64) on a trailing 12-month basis in Q2 FY27. | Number of >$1M customers exceeding 85 or >$10M customers exceeding 70 in Q2 FY27 = Bullish. | Company earnings press releases and conference calls. Investor presentations. | None directly applicable for specific customer counts. | Revelio Labs: Snowflake customer churn/expansion analysis (indirect). Thinknum: Enterprise software adoption trends. |
| Product Revenue Growth and Raised FY27 Guidance | Product revenue is the primary indicator of platform usage and top-line growth. A beat in Q1 FY27 product revenue and a raise in full-year guidance signal strong underlying demand and management's confidence in future performance, validating the AI-driven growth thesis. | Q2 FY27 product revenue actuals relative to the guidance range of $1.415 billion to $1.42 billion, and any further updates to the full FY27 product revenue guidance of $5.84 billion. | Q2 FY27 product revenue exceeding $1.42 billion or an upward revision of FY27 guidance = Bullish. | Company earnings press releases and conference calls (next scheduled for Q2 FY27 results, typically in August). SEC filings (Form 10-Q). | Financial news outlets (e.g., Reuters, Bloomberg), investor relations website. | Bloomberg Terminal: SNOW product revenue estimates, consensus changes. |
Key Reported Metrics
| Metric | Why It Matters | Last Period |
|---|---|---|
| Product Revenue Growth | As a consumption-based model, product revenue directly reflects customer usage and the success of AI product monetization. Accelerated growth signals strong demand and execution, which is critical for investor confidence. | 34% YoY growth |
| Remaining Performance Obligations (RPO) Growth | RPO indicates the total value of signed contracts not yet recognized as revenue. Strong RPO growth signals robust long-term customer commitments and provides visibility into future revenue streams, mitigating consumption volatility. | 38% YoY growth |
| Net New Customers Growth | This metric reflects Snowflake's ability to expand its customer base and acquire new logos. Strong growth indicates successful market penetration and a broadening foundation for future consumption and AI adoption. | 38% YoY growth |
Key QuestionsCan Snowflake sustain its accelerated product revenue growth, driven by the rapid adoption and monetization of AI products like Cortex Code and Snowflake Intell
Can Snowflake sustain its accelerated product revenue growth, driven by the rapid adoption and monetization of AI products like Cortex Code and Snowflake Intelligence, to meet or exceed its raised FY27 guidance of 31%?
- Question 2
Despite a slight deceleration in RPO growth to 38% and expected Q4 weighting for bookings, can Snowflake effectively convert its remaining performance obligations into consistent near-term consumption, mitigating the inherent volatility of its consumption-based model?
- Question 3
Can Snowflake continue to expand its non-GAAP operating margin to meet its raised FY27 guidance of 13.5%, effectively offsetting the lower gross margins of new AI products and the integration costs of acquisitions like Observe and Natoma through operational efficiencies and AI-driven productivity?
Rerating Thresholds
| Metric | What'S Needed For Rerating | Why It Matters | Earnings Date |
|---|---|---|---|
| Product Revenue | Product revenue growth must re-accelerate to 31% YoY or higher (implying a beat of at least $1.25B against the $1.20B guidance). Additionally, the AI revenue run rate needs to reach $150M+, and FY27 product revenue guidance must be set at 28%+ to signal growth stabilization. | Snowflake's premium valuation is currently penalized by decelerating growth and consumption volatility. Re-acceleration would prove that 'Phase 2' AI agents are driving incremental, high-value compute usage. This shifts the narrative from a cyclical data utility to an indispensable AI orchestration platform, justifying a higher EV/Sales multiple. | 2026-02-25 |
| Net Revenue Retention (NRR) | Stabilization at 127% or a reversal toward the 128%-130% range. Investors need definitive proof that the multi-quarter decline has bottomed. A beat of the 125% internal trend, coupled with guidance suggesting AI-driven expansion is finally outpacing legacy cloud optimizations, is required for a valuation rerating. | NRR validates Snowflake's 'data gravity' and the success of its AI pivot. Achieving this threshold proves that existing enterprises are scaling production AI workloads, shifting the narrative from 'cost optimization' to 'growth expansion,' which is critical for supporting a double-digit revenue multiple. | 2026-02-25 |
| Remaining Performance Obligations (RPO) | To trigger a valuation rerating, Snowflake needs to sustain RPO growth at or above the 50-55% YoY threshold, specifically driven by current RPO (cRPO) growth accelerating toward 30%. This must be accompanied by at least two additional nine-figure ($100M+) deal announcements and an AI revenue run rate update exceeding $140M, proving that the massive backlog is tied to high-value 'Phase 2' AI deployment rather than legacy storage. | RPO validates long-term 'data gravity' and enterprise commitment within Snowflake's volatile consumption model. Sustaining 50%+ growth proves the company is winning the AI orchestration battle against hyperscalers, providing the visibility needed to justify a return to a premium EV/Sales multiple above 12x. | 2026-02-25 |
Earnings Transcript Summary
· 2027Q1 Earnings Call
| 3 Things Management Is Most Focused On | Call Takeaway & Tone | Prior Quarter'S Y/Y Growth By Segment | 3 Things Analysts Most Pressed On (And Mgmt Responses) | Revenue Segments |
|---|---|---|---|---|
| 1. Accelerating AI-driven growth and adoption of AI products: Management emphasized that AI is fundamentally reshaping work and strengthening Snowflake by accelerating consumption in the core platform, with Snowflake Intelligence and Cortex Code (CoCo) seeing the fastest adoption in company history, and these AI products increasing core platform consumption. 2. Operational discipline and margin expansion: The company highlighted its continued focus on executing with discipline and operational rigor, leading to a Q1 non-GAAP operating margin expansion of over 300 basis points year-over-year to 12%. 3. Strengthening go-to-market execution and ecosystem: Management discussed strengthening the go-to-market organization under the new Chief Revenue Officer, Jonathan Boulier, and expanding strategic partner relationships, including a new $6 billion multiyear agreement with AWS and a $200 million partnership with OpenAI. | The overall takeaway of the call was highly positive and confident. Snowflake delivered strong Q1 FY27 results, with product revenue growth accelerating significantly to 34% year-over-year, driven by a powerful combination of strength in its core data platform and the rapid adoption and monetization of its AI capabilities, particularly Snowflake Intelligence and Cortex Code (CoCo). Management emphasized that AI is a secular tailwind, transforming Snowflake into the 'agentic control plane' for enterprises, connecting data, models, applications, and workflows in a trusted and governed environment. The tone was optimistic, highlighting rapid innovation, strong go-to-market execution, and operational discipline, leading to an increased FY27 outlook for both growth and margin expansion. | Product revenue grew 30% year-over-year in Q4 FY26. | 1. The inflection points driving the accelerated sequential dollar growth and full-year guidance raise: Sanjit Singh from Morgan Stanley asked about the market backdrop and the specific inflection points within Snowflake's portfolio. Management responded that AI is accelerating the value customers get from data, creating a healthy tailwind for the core data platform. They also highlighted that agentic products like Snowflake Intelligence and Cortex Code (CoCo) 'came into their own' in Q1, with CoCo, in particular, driving more consumption on the core data platform. 2. How Cortex Code (CoCo) changes customers' ability to leverage data faster and its impact on the go-to-market model: Kirk Materne from Evercore ISI inquired about CoCo's effect on customer efficiency and sales strategy. Management explained that CoCo, as a general-purpose coding agent specialized for Snowflake, significantly speeds up coding transformations and migrations. For go-to-market, they noted that products like Snowflake Intelligence have made the sales team 'AI native,' enabling solution engineers to build more realistic demos and prototypes quickly, and internal teams to achieve high productivity with CoCo. 3. Concerns about potential customer throttling of AI tool usage due to cost and the gross margin profile of AI products: Karl Keirstead from UBS questioned if customers might limit Cortex Code spend and the gross margin of these new AI offerings. Management acknowledged cost as an issue but emphasized the 'incredible value' these products create (10x faster task completion, enabling previously impossible tasks) and their efforts to build cost governance features like account-level limits. Brian Robins confirmed that AI products have a lower gross margin but stated that these are being offset by efficiencies, such as lower bandwidth costs from the AWS contract, to maintain the 75% non-GAAP product gross margin for the full year. | Product revenue grew 34% year-over-year. |
· 2026Q4 Earnings Call
| 3 Things Management Is Most Focused On | Call Takeaway & Tone | Prior Quarter'S Y/Y Growth By Segment | 3 Things Analysts Most Pressed On (And Mgmt Responses) | Revenue Segments |
|---|---|---|---|---|
| 1) Drive growth and margin expansion through continued AI investments and product velocity (Snowflake Intelligence, Cortex Code, 430 product capabilities launched this year). 2) Strengthen go-to-market execution and financial discipline to sustain product velocity (stable guidance framework; focus on sales execution). 3) Expand AI platform ecosystem and adoption (Observe acquisition; partnerships with SAP, Anthropic, OpenAI, Google Cloud; broader model availability; enabling customers to build AI-native workloads). | Takeaway: Snowflake remains at the center of the enterprise AI revolution, transitioning from a data platform to an AI-native orchestration platform with strong AI-driven growth signals and record large deals. Tone: confident, energized, and disciplined, with a clear focus on sustainable growth, product velocity, and margin expansion. | Product revenue grew 29% YoY in Q3 FY26 | 1) Durability of FY27 guide at 27% growth given consumption model; management said the guidance is anchored in stable core growth plus AI contribution, with Observe contributing about 1 percentage point, and that they rely on a strict, data-driven forecasting process. 2) The scale and sustainability of AI revenue including Snowflake Intelligence and Cortex Code adoption; management highlighted that Snowflake Intelligence is now used by over 2,500 accounts and Cortex Code has broad adoption (thousands of customers), emphasizing rapid production deployment and strong customer demand as evidence of durability. 3) The nature of the large deals and bookings momentum (e.g., the >$400 million deal); management noted it was with an existing customer and that there were multiple 9-figure deals this quarter; described it as evidence of durable trust and continuing product road-map momentum rather than a one-off event. | Product revenue grew 30% YoY in Q4 FY26. |
· 2026Q3 Earnings Call
| 3 Things Management Is Most Focused On | Call Takeaway & Tone | Prior Quarter'S Y/Y Growth By Segment | 3 Things Analysts Most Pressed On (And Mgmt Responses) | Revenue Segments |
|---|---|---|---|---|
| 1. AI Product Adoption and Monetization: Management highlighted reaching a $100 million AI revenue run rate one quarter early and the rapid adoption of Snowflake Intelligence (1,200 customers). 2. Strategic Ecosystem Partnerships: Emphasizing new and expanded deals with Anthropic (native model availability), SAP (data unification), and AWS ($2B marketplace milestone) to increase data gravity. 3. Large Enterprise Momentum: Focusing on high-value deals, evidenced by signing four nine-figure contracts and a record 615 new customers in the quarter. | Takeaway: Snowflake is successfully pivoting from a data storage provider to an AI-orchestration platform, with AI now influencing 50% of new bookings. The company is seeing strong 'agentic AI' traction and record-breaking large deal activity, allowing them to raise full-year revenue guidance. Tone: Highly confident, energetic, and disciplined. | Product Revenue: 30% y/y growth (Q2 FY26). (Note: Year-over-year growth slightly decelerated from 30% in Q2 to 29% in Q3). | 1. Guidance vs. Execution: Analysts questioned the Q4 sequential guide and the magnitude of the Q3 beat. Management responded that quarterly beats are less indicative than the raised full-year guidance and noted a $1M-$2M headwind from a hyperscaler outage. 2. AI Revenue Composition: Analysts asked for details on the $100M AI run rate. Management clarified it includes the Cortex suite (Search, Analyst) and Snowflake Intelligence, driven by production-level consumption rather than just pilots. 3. Operating Margin Fluctuations: Analysts noted the lower Q4 margin guide compared to Q3. Management explained that Q4 is impacted by the timing of annual guidance and front-loaded hiring, but reiterated their 9% full-year non-GAAP operating margin target. | Product Revenue: 29% y/y growth ($1.16 billion). |
Transcript Tidbits
| About Expanding Eligible Market | About Competition | About The Broader Industry | Where Things Are Headed | Updates On Theme | Broader Themes Emerging | Bullish-Leaning Quotes (Short) | Bearish-Leaning Quotes (Short) | Hiring |
|---|---|---|---|---|---|---|---|---|
| Snowflake Intelligence and Cortex Code (CoCo) are seeing the fastest adoption of any new products in company history, opening new opportunities for growth as the first major product surfaces of the agentic control plane. The intended acquisition of Natoma will extend the Snowflake agentic control plane beyond data development workflows into everyday applications, allowing users to send emails, summarize Slack conversations, check calendars, and open JIRA tickets without leaving Snowflake Intelligence or CoCo. This will extend Snowflake's leadership in AI governance by ensuring companies can safely manage not just their data, but also the actions AI agents take across business workflows. Snowflake announced an expanded collaboration with AWS through a new $6 billion multiyear agreement to accelerate enterprise AI adoption globally. They also announced an expanding $200 million partnership with OpenAI. The joint capability from their landmark partnership with SAP is now generally available, enabling customers to unite mission-critical business data across their core data systems within their AI data cloud. Snowflake is uniquely positioned to lead in the next phase of enterprise AI because they already sit at the center of customers' data, business context, AI models, and workflows. | Snowflake's unique value proposition emphasizes customer choice and independence from the mechanics of cloud providers, with implementations working on both AWS and Azure. They maintain successful partnerships with leading AI labs like Anthropic and OpenAI, collaborating to create great and safe AI products. Cortex Code and Snowflake Intelligence provide model choice, and the company always acts on behalf of what is right for the customer. Deep infrastructure capabilities such as role-based access control, world-class replication for disaster recovery, and robust organization support are difficult to develop and provide a significant competitive moat. Christian Kleinerman highlighted that Snowflake's existing security and governance configurations, including data masking and role-level policies, amplify the benefits of AI, whereas alternatives would require customers to rebuild these foundational elements. Snowflake is also rapidly developing new capabilities, powered by AI, at a fast pace. | AI is fundamentally reshaping how work gets done across industries. Organizations are moving toward a future where employees and intelligent agents work side by side to accelerate decisions, automate complex workflows, and unlock entirely new levels of productivity and innovation. The industry is rapidly evolving towards the 'agentic enterprise' and the 'agentic control plane'. The AI world is moving very fast, and the combination of trusted enterprise data, rich business context, leading AI models, and secure connectivity into enterprise applications creates unique opportunities. | Snowflake is positioned to lead in the era of the agentic enterprise. The company is increasing its FY '27 outlook from 27% to 31% year-over-year growth, driven by strength in its core data platform business and a meaningful uplift from AI capabilities, including CoCo and Snowflake Intelligence. They expect the momentum with CoCo to continue as adoption expands. The intended acquisition of Natoma will extend the Snowflake agentic control plane beyond data development workflows into everyday applications. Snowflake is also leading the AI transformation internally, using Snowflake Intelligence and CoCo to revolutionize how their teams work, for example, in support, site reliability engineering, and data organization. The company is strengthening its go-to-market organization under the new Chief Revenue Officer, Jonathan Boulier, to support its next phase of growth. They will continue to invest in key functions like sales and solution engineering, while leveraging AI automation to gain efficiencies in other areas such as support and technical documentation. Snowflake is implementing cost limits at the account or agent level for AI products to help customers manage expenses as usage scales. They are also building native capabilities within their coating agent products to efficiently use smaller models for simpler tasks, like summarizing Slack threads. The company is creating 'memory concepts' where the use of products within Snowflake makes Cortex Code itself better for future use, contributing to a flywheel effect. The cloud run time product is in public preview, enabling the execution of autonomous agents in a governed manner. The Model Context Protocol (MCP) and Natoma are significant as they bring the context of SaaS applications into Snowflake's AI products, enabling instant actions across business workflows from a governed environment. Sridhar Ramaswamy views a coding agent as an 'abstraction agent' that allows users to perform tasks at a high level, simplifying complex operations. | Phase | The 'agentic enterprise' and 'agentic control plane' are central concepts, representing a future where employees and intelligent agents collaborate to drive productivity and innovation. AI is creating a 'flywheel effect' where the adoption of new AI products like CoCo and Snowflake Intelligence accelerates consumption on the core data platform. The concept of 'abstraction agents' is emerging, where coding agents enable users to perform complex tasks at a high level, simplifying workflows. 'Cost governance' for AI products at scale is a critical emerging theme, with Snowflake developing controls like account-level and agent-level cost limits to manage expenses. | Product revenue came in at $1.334 billion with growth accelerating to 34% year-over-year, up from 30% last quarter and 26% a year ago, marking our strongest sequential dollar growth in company history. Our net revenue retention rate increased to 126%. Our Q1 non-GAAP operating margin expanded over 300 basis points year-over-year to 12%. We are increasing our FY '27 outlook from 27% to 31% year-over-year growth. Snowflake Intelligence and CoCo are seeing the fastest adoption of any new products in our history. Customers who are adopting CoCo are growing even faster. In Q1, 8 customers surpassed $10 million in trailing 12-month revenue. We now have 64 customers spending more than $10 million on a trailing 12-month basis. Accounts using Snowflake Intelligence more than doubled quarter-over-quarter. CoCo is already in use with more than 7,100 accounts. CoCo is contributing meaningful AI revenue while also driving increased engagement across the broader platform. We added 616 net new customers, up 38% year-over-year. The number of new cases, individual projects managed on Snowflake deployed in the quarter increased 114% year-over-year. The number of use cases on per account executive increased 86% year-over-year. We announced an expanded collaboration with AWS through a new $6 billion multiyear agreement. Snowflake surpassed $7 billion in lifetime AWS Marketplace sales. We now have 79 customers spending more than $1 million on a trailing 12-month basis. 46 customers crossed the 1 million threshold in Q1 compared to 26 in the year ago period. Remaining performance obligations grew 38% year-over-year. We are increasing our full year non-GAAP operating margin guidance from 12.5% to 13.5%. | Our AI products have a lower gross margin than our core platform. The one thing that we want to do with our AI products when we launch a new product like CoCo is make sure that we develop a great product that we get massive adoption. Our full year outlook for both non-GAAP operating margin and non-GAAP adjusted free cash flow margin continues to include approximately 150 basis point headwind related to our Observe acquisition. | Strong revenue growth and disciplined hiring both contributed to the outperformance in non-GAAP operating margin. We added 190 employees this quarter compared to approximately 400 added in the year ago period. Of these 190 employees, 173 joined Snowflake through the Observe acquisition. Excluding Observe, organic hiring was limited to 17 people in the quarter. Our intended acquisition of Natoma will bring 20 employees to Snowflake. AI is transforming how we operate internally, enabling greater productivity through a combination of slower hiring and more cloud spend. We will continue to invest in key functions like sales and solution engineering, but this is counterbalanced by significant efficiencies gained through AI automation in other functions such as support, site reliability engineering (SRE), and technical documentation. |
| About Expanding Eligible Market | About Competition | About The Broader Industry | Where Things Are Headed | Updates On Theme | Broader Themes Emerging | Bullish-Leaning Quotes (Short) | Bearish-Leaning Quotes (Short) | Hiring |
|---|---|---|---|---|---|---|---|---|
| Snowflake Intelligence and Cortex Code are driving the company's evolution from a data governance and analysis platform to one for building and running AI-native applications and workflows. The general availability of Snowflake OpenFlow makes it easier to bring diverse data types into the platform, while Snowflake Postgres (now generally available) transforms Snowflake into a platform for building and running production-grade transactional applications. The acquisition of Observe expands Snowflake's opportunity into the $50 billion IT operations market, positioning it to lead in next-generation AI-powered observability. Strategic partnerships with SAP, Anthropic, OpenAI, and Google Cloud (Gemini models) further expand model choice and integration for customers. Snowflake's interoperability strategy supports open data ecosystems like Iceberg, allowing SQL queries on any open data and enabling Snowflake Intelligence agents to be used by other agents. | AI is reshaping the software landscape, redefining categories and competitive dynamics, creating a clear separation between systems that demonstrate intelligence and platforms that can deploy it safely and at scale. Snowflake aims to be the winning platform by combining trusted enterprise data, governed business metrics, secure execution, and broad model choice. The company emphasizes its 'secret sauce' of packaging these capabilities into a cohesive, easy-to-use product. While acknowledging multiple top model providers, Snowflake works with all of them. Despite many vendors trying to be the go-to for building agents, Snowflake believes its position as the steward of customers' most important data provides a unique advantage. Interoperability is also a key competitive strategy, ensuring customers have options and are not locked in. | The past year has been transformative, with the promise of AI becoming a reality, placing Snowflake at the center of the enterprise AI revolution. AI is reshaping the software landscape, redefining categories and competitive dynamics. AI agents are becoming central to how work gets done, making capabilities like data access, governance, and security even more valuable. The enterprise is heading towards an 'agentic era,' where Snowflake believes it is uniquely positioned to become the control plane. Overall, the winners in this era will be companies that provide a single source of enterprise truth. | Snowflake is rapidly innovating to support enterprises across their data life cycle, transforming from a platform for governing and analyzing data into one where customers build and run AI-native applications and workflows. The company sees immense opportunity, particularly with products like Snowflake Postgres enabling transactional applications and the Observe acquisition expanding into the $50 billion IT operations market for AI-powered observability. Management expects a long runway of durable high growth and continued margin expansion. The vision is for Snowflake to become the control plane for the 'agentic era,' with every employee having access to agents providing key business details. Snowflake plans to introduce features like per-user caps on Snowflake Intelligence to offer price predictability alongside consumption-based pricing. | Cloud | The enterprise AI revolution is moving from promise to reality, fundamentally reshaping the software landscape and redefining competitive dynamics. The emergence of 'agentic AI' is central, with AI agents automating complex workflows and potentially replacing traditional software systems. A critical broader theme is the need for a 'single source of enterprise truth' combined with robust governance, security, and broad model choice for effective AI deployment. The industry is also seeing the expansion of observability into 'next-generation AI-powered observability' driven by AI. | Product revenue in Q4 grew 30% year-over-year to reach $1.23 billion. Remaining performance obligations totaled $9.77 billion with year-over-year growth accelerating to 42%. Our net revenue retention was at a healthy 125%. Fiscal '26 non-GAAP operating margin reached 10.5%, expanding more than 400 basis points year-over-year. Stock-based compensation declined meaningfully from 41% of revenue in fiscal '25 to 34% in fiscal '26, and we expect it to further decrease to 27% of revenue in fiscal '27. We added 2,332 net new customers this year. This quarter, we delivered the largest sequential increase in accounts using AI, bringing the total to more than 9,100 accounts. Snowflake Intelligence has scaled from a nascent offering to an essential capability for over 2,500 accounts, almost doubling quarter-over-quarter. Cortex Code... is already helping over 4,400 customers build and scale AI-powered applications. We launched over 430 product capabilities, underscoring the strength of our product velocity. We signed the largest deal in Snowflake's history, greater than $400 million in total contract value and signed 7 9-figure contracts compared to 2 in the same period last year. We delivered another strong quarter of new customer wins, adding 740 net new customers, up 40% year-over-year. We now have 733 customers spending more than $1 million... growing 27% year-over-year. A record number of customers crossed $10 million... bringing a total of 56 customers above this $10 million threshold, growing 56% year-over-year. AI has really changed the framework for investing in growth. It's no longer tied to headcount. | The margin profile for those [new AI products] right now aren't as high as the core business. We expect product revenue of approximately $5.66 billion, representing 27% year-over-year growth. We expect FY '27 non-GAAP product gross margin of 75%. This includes an approximate 150 basis point headwind related to our acquisition. There is also a risk of maybe sticker shock as AI agents proliferate. | Our hiring this year will be weighted to the first quarter, reflecting the addition of 178 employees from Observe. In Q4, we had a small reduction in force and about 200 people in the company were impacted, resulting in only 37 net new headcount additions. AI has fundamentally changed the framework for investing in growth, as it is no longer tied to headcount. |
| About Expanding Eligible Market | About Competition | About The Broader Industry | Where Things Are Headed | Updates On Theme | Broader Themes Emerging | Bullish-Leaning Quotes (Short) | Bearish-Leaning Quotes (Short) | Hiring |
|---|---|---|---|---|---|---|---|---|
| Snowflake is expanding its TAM by moving into transactional workloads with the upcoming GA of Postgres support and the Unistore HTAP product. The company reached a $100 million AI revenue run rate a quarter early, driven by the 'fastest ramp in product adoption' for Snowflake Intelligence (agentic AI), which already has 1,200 customers. Strategic partnerships with SAP, Anthropic, and Workday, along with the acquisition of Datometry for legacy migrations, are opening new enterprise data silos. | Snowflake is positioning its 'zero copy' and bidirectional data sharing agreements with SaaS leaders like Salesforce, SAP, and ServiceNow as a competitive advantage that creates a 'single pane of glass' for customers. The CEO noted that while hyperscalers face outages, Snowflake's disaster recovery seamlessly moved 300 mission-critical workloads. They are also competing for the 'AI budget,' noting a narrative shift where Snowflake is now viewed as the cornerstone of enterprise AI strategies. | The industry is seeing a 'narrative shift' where data budgets are becoming explicitly tied to AI budgets. Management cited AWS commentary that the industry is only 15% to 20% through the legacy on-prem to cloud migration journey. There is a broader trend toward 'agentic AI' where enterprises move from simple chatbots to complex agents that handle tasks previously requiring multiple full-time employees. | Snowflake aims to make every dataset in the platform 'AI-ready,' shifting from sharing datasets to sharing 'agents' on top of data. Future growth is expected from the 'pull-push' effect of AI accelerating legacy migrations. The company is also heading toward a more balanced 'efficient growth' model, focusing on high durable growth alongside margin expansion and upskilling its workforce to be AI-native. | Cloud | Agent-to-agent collaboration; convergence of data and AI budgets; 'Zero-copy' data sharing becoming an industry standard for SaaS interoperability. | AI influencing 50% of the bookings signed this quarter; fastest ramp in product adoption in our company history; $100,000,000 in AI revenue run rate, achieved one quarter earlier than anticipated; record 615 new customers this quarter. | Hyperscaler outage, which impacted our revenue by approximately $1,000,000 to $2,000,000; large migrations are lumpy and not all that easy to predict; 4Q operating margin was guided maybe a couple of points below where you guided 3Q. | Snowflake front-loaded sales and marketing hiring in the first half of the year and is now focused on the 'maturation' and upskilling of that workforce. Accenture has launched a Snowflake business group to train 5,000 professionals. Internally, the company is rolling out 'coding agents' to help solution engineers and reps create custom demos more efficiently. |
Earnings ResultsProduct revenue grew 30% year-over-year, an acceleration from the prior quarter's 29% but still below the 31% rerating threshold. The reported $1.23 billion bea
| Metric | Prior Quarter | Rerating Trigger | Actual Reported | Hit Target? | Notes |
|---|---|---|---|---|---|
| Product Revenue | 29% | Product revenue growth must re-accelerate to 31% YoY or higher (implying a beat of at least $1.25B against the $1.20B guidance). Additionally, the AI revenue run rate needs to reach $150M+, and FY27 product revenue guidance must be set at 28%+ to signal growth stabilization. | Q4 Product Revenue: $1.23 billion (30% y/y growth); FY27 Product Revenue Guidance: $5.66 billion (27% y/y growth) | No | Product revenue grew 30% year-over-year, an acceleration from the prior quarter's 29% but still below the 31% rerating threshold. The reported $1.23 billion beat the guidance range of $1.195B - $1.200B, but not by the magnitude required for a rerating (which was >4% or $1.248B+). The FY27 product revenue guidance of 27% year-over-year growth also fell short of the 28%+ rerating threshold. A specific AI revenue run rate update exceeding $150M was not explicitly provided in the transcript, although the company noted a significant increase in accounts using AI. |
| Net Revenue Retention (NRR) | 127% | Stabilization at 127% or a reversal toward the 128%-130% range. Investors need definitive proof that the multi-quarter decline has bottomed. A beat of the 125% internal trend, coupled with guidance suggesting AI-driven expansion is finally outpacing legacy cloud optimizations, is required for a valuation rerating. | 125% | No | Net revenue retention was reported at 125%, which is a decline from the prior quarter's 127% and did not meet the rerating trigger of stabilization at 127% or a reversal towards the 128%-130% range. This indicates that the multi-quarter decline has not bottomed, and AI-driven expansion is not yet outpacing legacy cloud optimizations to the extent required for a valuation rerating. |
| Remaining Performance Obligations (RPO) | 55% | To trigger a valuation rerating, Snowflake needs to sustain RPO growth at or above the 50-55% YoY threshold, specifically driven by current RPO (cRPO) growth accelerating toward 30%. This must be accompanied by at least two additional nine-figure ($100M+) deal announcements and an AI revenue run rate update exceeding $140M, proving that the massive backlog is tied to high-value 'Phase 2' AI deployment rather than legacy storage. | $9.77 billion (42% y/y growth) with 7 nine-figure deals announced. | Partially | Remaining performance obligations totaled $9.77 billion with year-over-year growth accelerating to 42%, which was below the 50-55% rerating threshold. However, the company signed 7 nine-figure contracts, including the largest deal in Snowflake's history (greater than $400 million), significantly exceeding the 'at least two' additional nine-figure deals required for a rerating. A specific AI revenue run rate update exceeding $140M was not provided in the transcript. The acceleration in RPO growth and the record number of large deals indicate strong customer commitment to Snowflake's platform and AI strategy. |
Notes
| Date | Comment | Comment Type | Comment Sentiment | Link | IS CHANGE | Price Reaction |
|---|---|---|---|---|---|---|
| 2026-02-25 | Snowflake reported strong Q4 FY26 results, with product revenue up 30% and RPO accelerating to 42%, driven by robust AI product adoption and record bookings. Despite beating estimates and providing solid FY27 guidance, the market reacted negatively, with the stock falling post-earnings. This suggests investors prioritized concerns over GAAP losses, cautious outlook, and recent legal challenges, contradicting the company's positive messaging on AI-driven growth and efficiency. | Other | Neutral | False | +0.00% (vs SPY: +0.00%) |
Upcoming Events
| Catalyst ID | Estimated Timing | Estimated Date Start | Estimated Date End | Catalyst | Why It Matters | Ticker Or Theme Specific | Transcript Date | Source Type |
|---|---|---|---|---|---|---|---|---|
| SNOW_a0f274f7 | next call | 2026-03-01 | 2026-03-01 | Fiscal Year 2027 Guidance and Q4 Fiscal 2026 Results | Management stated that consumption behavior in January and February is the primary input for FY27 guidance; a strong guide would validate the sustainability of the 28% growth rate and AI revenue momentum. | Ticker | 2025-12-03 | |
| SNOW_aee8fb9d | couple of more months | 2026-02-01 | 2026-02-01 | General Availability (GA) of Postgres support | Integrating Postgres (via Crunchy Data) allows Snowflake to handle OLTP workloads, which is essential for supporting the transactional data needs of advanced agentic AI applications. | Ticker | 2025-12-03 | |
| SNOW_b9f17a4c | upcoming Olympic games | 2026-02-06 | 2026-02-06 | USA Bobsled Skeleton Olympic performance using Snowflake Intelligence | This serves as a high-profile, real-time proof of concept for Snowflake's agentic AI capabilities in optimizing complex performance data under extreme conditions. | Ticker | 2025-12-03 | |
| SNOW_e0cf2535 | through March 2027 | 2027-03-01 | 2027-03-01 | Expiration of $4.5 billion share repurchase authorization | With $1.3 billion remaining, the pace of buybacks impacts share count and reflects management's view on the stock's valuation and capital allocation priorities. | Ticker | 2025-12-03 | |
| SNOW_218922ea | over the next few years | 2026-01-01 | 2026-01-01 | Ongoing legacy on-premise data warehouse migrations | Management cited industry estimates that only 15-20% of migrations are complete; Snowflake's ability to capture this remaining 80% is critical for long-term durable growth. | Industry/Macro | 2025-12-03 | |
| SNOW_ad9d11be | Recently agreed to acquire | 2026-01-01 | 2026-01-01 | Integration of SelectStar technology into Snowflake Horizon | The acquisition is intended to enhance the Horizon catalog with richer data context, which is a prerequisite for making agentic AI tools like Snowflake Intelligence more accurate and reliable. | Ticker | 2025-12-03 | |
| SNOW_1ea4a65f | we will be launching features like a per user cap on top of Snowflake Intelligence | 2026-03-01 | 2026-07-31 | Launch of per-user and account caps for Snowflake Intelligence to provide price predictability for AI agent usage. | This feature aims to alleviate customer concerns about consumption costs, potentially driving wider adoption of Snowflake Intelligence and AI agents on the platform, which could positively impact revenue and investor sentiment. | Ticker | 2026-02-25 | earnings_transcript |
| SNOW_3568200a | the week of June 1 in San Francisco | 2026-06-01 | 2026-06-07 | Snowflake's Investor Day and Summit Conference. | This event serves as a platform for management to provide updates on product roadmap, strategic direction, and financial outlook, which could materially impact investor sentiment and valuation based on any new announcements or revised guidance. | Ticker | 2026-02-25 | earnings_transcript |
| SNOW_02751c2d | intended acquisition of Natoma | 2026-06-01 | 2026-09-30 | Completion of Snowflake's intended acquisition of Natoma. | This acquisition is expected to extend Snowflake's agentic control plane into everyday applications, enhancing AI governance and potentially driving new growth opportunities and customer adoption, impacting product capabilities and competitive positioning. | Ticker | 2026-05-27 | earnings_transcript |
| SNOW_5ad694ee | next week | 2026-06-03 | 2026-06-07 | New product announcements, strategic updates, or revised long-term financial targets presented at Snowflake Summit and Investor Day. | These announcements could materially impact investor sentiment, future guidance, and competitive positioning, especially regarding AI product development, market strategy, and long-term financial outlook. | Ticker | 2026-05-27 | earnings_transcript |
| SNOW_9276e08c | we are creating the controls that one needs in order to keep costs manageable as things continue expanding. | 2026-05-01 | 2027-01-31 | Successful implementation and adoption of AI cost governance features (e.g., cost limits, token restrictions) for Snowflake Intelligence and Cortex Code. | Effective cost controls are crucial to mitigate 'sticker shock' and encourage broader enterprise adoption of AI products, directly influencing customer spending, retention, and ultimately, Snowflake's revenue and investor sentiment. | Ticker | 2026-05-27 | earnings_transcript |
| SNOW_13ac6380 | for FY '27 | 2026-02-01 | 2027-01-31 | Snowflake's ability to achieve and maintain its guided non-GAAP product gross margin of 75% for fiscal year 2027, despite the lower gross margin profile of AI products. | Successfully maintaining gross margins would demonstrate strong operational efficiency and cost management, positively impacting profitability and investor confidence. Failure could lead to margin pressure and negative investor sentiment. | Ticker | 2026-05-27 | earnings_transcript |