Can you describe the $400M+ deal and if there are sustainable new drivers for the robust bookings and RPO figures?

Sridhar attributed strong bookings to customer trust and product velocity. Brian clarified the $400M+ deal was with an existing customer, and 7 nine-figure contracts were signed in Q4, indicating strong customer buy-in on Snowflake's product roadmap and AI strategy. “Bookings and multiyear contracts are a clear indication of the trust that our partners have in their future with Snowflake.”

How does Observe fit into the $50 billion observability market, and what was the rationale for the acquisition?

Sridhar explained that observability, especially for AI, is a critical data problem. Observe, built on Snowflake, offers significant efficiency advantages for customers with large data volumes, and there's a substantial overlap between Observe's potential customers and Snowflake's existing base, making integration straightforward. “Observe was built on top of Snowflake. So it inherits the excellent data and compute foundation that Snowflake has.”

How is Snowflake working with customers to reduce the risk of 'sticker shock' as AI agents proliferate and consumption increases?

Sridhar emphasized Snowflake's consumption-based, predictable model, citing internal ROI examples. He stated plans to launch features like per-user caps on Snowflake Intelligence to offer price predictability, combining consumption pricing with clear upper limits to charges. “We will be launching features like a per user cap on top of Snowflake Intelligence, so they can feel like there is a clear upper limit to how much they can get charged with an agent.”

SNOW

Snowflake (SNOW) Q4 FY26 earnings call: guidance and Q&A

Earnings call· Jan 2026 (Q4 FY26)· Information Technology· Feb 25, 2026

Source: earnings call transcript

Executive summary

Snowflake Q4 FY26 — AI-driven Growth and Operational Efficiency

Snowflake concluded Q4 FY26 with strong performance, driven by the enterprise AI revolution and its evolving platform for AI-native applications. The company demonstrated robust RPO growth and significant margin expansion, reflecting both core business strength and increasing AI workload contributions. Strategic product innovations and partnerships are fueling customer adoption and operational efficiencies, positioning Snowflake for continued durable growth and efficient scaling in the agentic era.

Highlights

Product revenue grew 30% year-over-year to $1.23 billion.
Remaining performance obligations (RPO) accelerated to 42% year-over-year growth, reaching $9.77 billion.
Non-GAAP operating margin expanded over 400 basis points year-over-year to 10.5%.
Added 740 net new customers in Q4, up 40% year-over-year, including 15 Global 2000 organizations.
Net revenue retention remained healthy at 125%.

Concerns

FY27 non-GAAP product gross margin is guided at 75%, a decline from FY26's 75.8%.
FY27 non-GAAP adjusted free cash flow margin guidance of 23% includes an approximate 150 basis point headwind related to the Observe acquisition.
A small reduction in force impacted approximately 200 people in Q4 FY26, though framed as AI-driven efficiency.

Guidance & targets

Category	Target	Timeline	Confidence
Q1 FY27 Product Revenue	$1.262 billion to $1.267 billion high materiality	Q1 · FY27	High
FY27 Product Revenue	approximately $5.66 billion high materiality	FY27	High
FY27 Product Revenue Growth (Observe contribution)	approximately 1 percentage point medium materiality	FY27	High
FY27 Non-GAAP Product Gross Margin	75% high materiality	FY27	High
Q1 FY27 Non-GAAP Operating Margin	9% medium materiality	Q1 · FY27	High
FY27 Non-GAAP Operating Margin	12.5% high materiality	FY27	High
FY27 Non-GAAP Adjusted Free Cash Flow Margin	23% high materiality	FY27	High
FY27 Stock-based compensation as % of revenue	27% medium materiality	FY27	High

SNOW operating KPIs by quarter

SNOW operating KPIs stated on its earnings calls, by fiscal quarter
KPI	Jan 2025 Q4 FY25	Jul 2025 Q2 FY26	Oct 2025 Q3 FY26	This call Jan 2026 Q4 FY26	Apr 2026 Q1 FY27	Jul 2026 Q2 FY27	Change vs prior quarter
Remaining performance obligation (RPO)	$6.9B Remaining performance obligations totaled $6.9 billion with year-over-year growth of 33%. Source: earnings call transcript	$6.9B Remaining performance obligations totaled $6.9 billion with year-over-year growth of 33%. Source: earnings call transcript	$7.88B Remaining performance obligations totaled $7.88 billion, with year-over-year growth accelerating to 37%. Source: earnings call transcript	$9.77B Remaining performance obligations totaled $9.77 billion with year-over-year growth accelerating to 42%. Source: earnings call transcript	—	$9B Remaining performance obligations grew 30% year-over-year, totaling $9 billion. Source: earnings call transcript	—
Net revenue retention rate	126% Our net revenue retention was a very healthy 126%. Source: earnings call transcript	125% Our net revenue retention rate was a very healthy 125%. Source: earnings call transcript	125% Our net revenue retention remained stable at a very healthy 125% and we added a record 615 new customers this quarter. Source: earnings call transcript	125% Our net revenue retention was at a healthy 125%. Source: earnings call transcript	—	126% Within our existing base, customer expansion is healthy, as evidenced by our net revenue retention rate of 126%. Source: earnings call transcript	—
Customers AI and ML technology weekly users	4,000+ We now have over 4,000 customers using our AI and ML technology on a weekly basis. Source: earnings call transcript	6,100+ And once they are on our platform, AI becomes a cornerstone of their strategy, powering 25% of all deployed use cases with over 6,100 accounts using Snowflake's AI every week. Source: earnings call transcript	7,300+ In Q3, more than 7,300 accounts are using our AI capabilities every week. Source: earnings call transcript	—	—	—	—
Customers	—	—	—	13.3K+ This year's results are a testament that the AI Data Cloud continues to deliver tremendous value to our more than 13,300 customers across every stage of the data life cycle. Source: earnings call transcript	13.912K Our 13,912 customers start to Snowflake because our AI data cloud is easy to use, seamlessly connected for collaboration, entrusted with enterprise-grade governance and security. Source: earnings call transcript	14.554K Snowflake now provides the data and AI foundation for 14,554 customers around the world. Source: earnings call transcript	+4.6%
Customers Global 2000	—	—	776 Our Global 2000 customers now totaled 776 with each of these accounts spending, on average, $2.3 million on a trailing 12-month basis. Source: earnings call transcript	—	—	829 We added 14 net new Global 2000 customers, bringing our total to 829. Source: earnings call transcript	—
Customers Cortex Code	—	—	—	4,400+ It's a truly transformational coding agent that's already helping over 4,400 customers build and scale AI-powered applications and massively accelerating their ability to deploy production-grade AI. Source: earnings call transcript	7,100+ And CoCo is already in use with more than 7,100 accounts, giving builders a natural language way to create applications, pipelines, agents and workloads directly in Snowflake. Source: earnings call transcript	—	—
Customers above an annual spend threshold >$1M TTM	—	—	—	733 We now have 733 customers spending more than $1 million on a trailing 12-month basis, growing 27% year-over-year and a record number of customers crossed $10 million in trailing 12-month spend, bringing a total of 56 customers above this $10 million threshold, growing 56% year-over-year. Source: earnings call transcript	79 We now have 79 customers spending more than $1 million on a trailing 12-month basis. Source: earnings call transcript	828 We now have 828 customers spending above the $1 million threshold. Source: earnings call transcript	+948.1%
Customers above an annual spend threshold >$10M TTM	—	—	—	56 We now have 733 customers spending more than $1 million on a trailing 12-month basis, growing 27% year-over-year and a record number of customers crossed $10 million in trailing 12-month spend, bringing a total of 56 customers above this $10 million threshold, growing 56% year-over-year. Source: earnings call transcript	64 We now have 64 customers spending more than $10 million on a trailing 12-month basis. Source: earnings call transcript	65 In fact, 65 customers have now crossed $10 million in trailing 12-month product revenue, demonstrating how our largest customers continue to go all in on Snowflake. Source: earnings call transcript	+1.6%

Operating figures the company stated on at least two of the calls shown, checked against each call's transcript. Click a figure to read the sentence. A dash means it was not stated that quarter.

Orderbook & backlog

Remaining Performance Obligations (RPO) $9.77 billion Q4 FY26

42% YoY growth

Accelerated for the second consecutive quarter.

Largest Deal Total Contract Value (TCV) greater than $400 million Q4 FY26

Signed with an existing financial services customer, representing the largest deal in Snowflake's history.

Nine-figure contracts signed 7 Q4 FY26

vs 2 in the same period last year

Represents strong commitments to Snowflake's strategic role in customers' long-term data and AI strategies.

Product announcements

Product	Type	Timeline
Snowflake Intelligence	launch	Q4 FY26
Cortex Code	launch	Q4 FY26
Cortex Code CLI	expansion	Q4 FY26
Snowflake OpenFlow	launch	Q4 FY26
Snowflake Postgres	launch	Q4 FY26

Deals & partnerships

Observe acquisition approximately $600 million

Acquired in a combination of cash and stock. Observe is a market-leading observability platform built on Snowflake, extending Snowflake's value into the $50 billion IT operations market and positioning for AI-powered observability.

SAP partnership

Landmark partnership focused on uniting mission-critical business data.

Anthropic partnership

Deepened partnership, enabling customers to apply direct AI capabilities using Anthropic's cloud model.

OpenAI partnership $200 million

Expanded partnership bringing OpenAI's models natively into Snowflake.

Google Cloud partnership

Customers now have access to the latest Gemini models natively within Snowflake.

Risks & headwinds

Non-GAAP product gross margin decline FY27

FY27 guidance of 75% vs FY26 actual of 75.8%

Mitigation:Balancing growth with efficiency; optimizing margins for new products after launch; finding more efficiencies in the core business.

Free cash flow margin headwind from acquisition FY27

150 basis point headwind

Mitigation:The impact is included in the FY27 guidance of 23% non-GAAP adjusted free cash flow margin.

Reduction in force Q4 FY26

approximately 200 people impacted

Mitigation:Framed as AI-driven efficiency, allowing for investment in growth without being tied to headcount.

Q&A highlights

What gives confidence in the sustained 27% growth guide for FY27, and what is the momentum like for Snowflake Intelligence and other non-core AI products?

Brian stated the guidance is based on stable core business growth, increasing AI workload contribution, and the Observe acquisition. Sridhar highlighted Snowflake Intelligence (2,500 customers) and Cortex Code (4,400 customers) as major growth drivers, accelerating the entire data lifecycle and transforming how customers use Snowflake.

“Cortex Code is the real game changer for us because it is a massive accelerant for every part of the data life cycle.”

asked by Sanjit Singh (Morgan Stanley) · answered by Sridhar Ramaswamy

2 min read 6 chapters

Detailed narrative

AI Revolution and Platform Evolution

Snowflake is positioning itself at the center of the enterprise AI revolution, evolving from a platform for data governance and analysis to one for building and running AI-native applications and workflows. This transformation is driven by the belief that successful AI platforms must combine trusted enterprise data, govern business metrics, ensure secure execution, and offer broad model choice.

The company's strategy focuses on delivering a data foundation that supports mission-critical workloads and enables AI agents to access data with robust governance and security.

Product Innovation and Velocity

The company demonstrated significant product velocity in FY26, launching over 430 product capabilities. Key general availability releases include Snowflake OpenFlow, simplifying the ingestion of structured, unstructured, batch, or streaming data, and Snowflake Postgres, a world-class operational database built directly onto the Snowflake platform for transactional applications. These innovations aim to broaden data flow into Snowflake and deepen application development capabilities.

Strategic Partnerships and Ecosystem Expansion

Snowflake is actively strengthening its ecosystem through strategic partnerships. A landmark partnership with SAP helps customers like Expand Energy unite mission-critical business data. Deepened collaboration with Anthropic assists customers like Intercom in automating customer support. The company also announced a $200 million expanded partnership with OpenAI and integration with Google Cloud's Gemini models, providing customers with native access to leading AI models within Snowflake for faster innovation and secure data governance.

Operational Efficiency and AI Impact

Internally, Snowflake is leveraging its own AI products, Snowflake Intelligence and Cortex Code, to drive measurable operational efficiencies. Service delivery teams are completing customer projects up to 5x faster, improving response accuracy by over 25%, and compressing implementation cycles. Site reliability engineering investigations are now resolved in minutes, and sales agents are projected to recoup the equivalent of 90 full-time engineers of productivity this year.

The finance team anticipates millions in annual savings from automating travel and expense analysis.

Observe Acquisition and Market Expansion

Snowflake closed the acquisition of Observe for approximately $600 million in cash and stock, extending its reach into the $50 billion IT operations market. Observe, built on Snowflake, integrates observability directly with data and AI products, reducing complexity and enabling faster, more reliable operations.

This acquisition is expected to unlock new expansion opportunities within Snowflake's customer base, particularly for those with large data volumes seeking more efficient observability solutions.

Customer Adoption and AI Use Cases

The company highlighted several customer successes, including Seagate modernizing its data foundation and Capital One scaling its AI initiatives using Snowflake. Toyota Motor Europe is leveraging Snowflake Intelligence for enterprise search and contract management, reducing AI agent deployment from months to weeks.

United Rentals uses Snowflake Intelligence to power a new business intelligence agent and Cortex Code to accelerate AI agent development, demonstrating the platform's ability to drive real-time decision-making and accelerate AI-powered applications.

Summary of the company's earnings call; see how call summaries are prepared. Not investment advice.