Snowflake and Anthropic expanded their partnership with a $200 million, multi-year agreement that integrates Claude AI models directly into Snowflake’s platform for 12,600+ global customers. The deal focuses on agentic AI deployment, enabling enterprises to analyze structured and unstructured data using natural language queries while maintaining strict security and governance standards. Claude powers Snowflake Intelligence and Cortex AI, delivering 90%+ accuracy on complex text-to-SQL tasks and processing trillions of tokens monthly. This partnership positions both companies at the forefront of enterprise AI adoption, particularly for regulated industries requiring production-ready AI agents.
Snowflake and Anthropic announced a $200 million, multi-year partnership on December 3, 2025, dramatically expanding Claude AI’s reach across global enterprises. The deal brings Anthropic’s advanced language models to Snowflake’s 12,600+ customers across Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Azure, establishing a joint go-to-market initiative focused on deploying AI agents at enterprise scale.
The Snowflake-Anthropic partnership is a $200 million, multi-year agreement that integrates Claude AI models into Snowflake Cortex AI and Snowflake Intelligence, enabling enterprises to query structured and unstructured data using natural language while maintaining rigorous governance and security standards.
What the Snowflake-Anthropic Partnership Delivers
The $200M Deal Breakdown
The expanded partnership represents one of Snowflake’s most significant strategic alliances, placing Anthropic in “a very select group of partners where we have nine-figure alignment,” according to Snowflake CEO Sridhar Ramaswamy. Beyond model integration, the agreement establishes joint sales efforts and co-innovation at the product level, with both companies committing engineering resources to optimize Claude for enterprise data environments.
Thousands of Snowflake customers already process trillions of Claude tokens per month through Snowflake Cortex AI, demonstrating proven market demand before this formal expansion. The partnership builds on earlier integration work that made Claude 3.5 Sonnet available in Cortex AI in January 2025.
Who Benefits from This Integration
Enterprise organizations in regulated industries financial services, healthcare, and life sciences gain the most immediate value from this partnership. These sectors require AI solutions that can handle sensitive data while maintaining compliance frameworks, audit trails, and governance controls. Snowflake’s governed data environment combined with Claude’s reasoning capabilities enables these organizations to move AI agents from pilot projects to full production deployment with confidence.
Data engineering teams, business analysts, and developers working within the Snowflake ecosystem can now access frontier AI models using familiar interfaces like SQL, Python, and REST APIs without moving data outside their security perimeter.
How Claude AI Powers Snowflake’s Enterprise Platform
Snowflake Intelligence Gets Claude Sonnet 4.5
Claude Sonnet 4.5 serves as the core reasoning engine for Snowflake Intelligence, an enterprise intelligence agent that answers questions using both structured and unstructured data through natural language queries. Business users can ask questions in plain English “What were our top-performing products in Q3 across EMEA markets?” and Claude determines what data sources are needed, pulls information from across the Snowflake environment, and delivers comprehensive answers.
This represents a fundamental shift from traditional business intelligence tools that require users to understand data schemas, write SQL queries, or navigate pre-built dashboards. Snowflake Intelligence brings AI directly to where enterprise data already lives, eliminating data movement and associated security risks.
Multimodal Analysis Through Cortex AI
Through Snowflake Cortex AI Functions, customers can leverage Claude models including Claude Opus 4.5, which Snowflake hosted on day one of its release to query text, images, audio, and traditional tabular data, all using SQL. This multimodal capability allows enterprises to analyze customer service transcripts, product images, financial documents, and operational databases within a single unified workflow.
Claude Opus 4.5 delivers frontier performance with dramatically improved token efficiency, making it particularly effective for coding tasks, autonomous agents, and computer use applications. Data teams can access these models through the Cortex Playground interface for testing prompts and comparing model outputs before deploying to production.
Building Custom AI Agents with Cortex Agents
Snowflake Cortex Agents enables customers to build production-ready data agents powered by Claude that retrieve and reason over both structured and unstructured data with built-in accuracy and efficiency. Unlike traditional chatbots that simply retrieve information, these agents can execute multi-step analysis, show their reasoning process, and maintain context across complex workflows.
A wealth management firm, for example, can deploy an agent that synthesizes client holdings with real-time market data and compliance rules to generate personalized portfolio recommendations all within Snowflake’s security and governance perimeter. The agent doesn’t just fetch data; it analyzes relationships, applies business logic, and explains its recommendations.
Real-World Performance: What the Numbers Show
90%+ Accuracy on Complex Text-to-SQL Tasks
Claude achieves greater than 90% accuracy on complex text-to-SQL tasks according to Snowflake’s internal benchmarks, significantly outperforming typical enterprise AI implementations. This high accuracy rate is critical for production environments where incorrect data queries can lead to flawed business decisions or compliance violations.
The model’s advanced reasoning capabilities and strong knowledge retention give Snowflake confidence in powering enterprise-grade applications, according to Arun Agarwal, Lead Product Marketing Manager for Cortex AI. Claude 3.5 Sonnet’s high coding proficiency enables it to translate natural language questions into precise SQL queries across complex database schemas.
Trillions of Claude Tokens Processed Monthly
Thousands of Snowflake customers collectively process trillions of Claude tokens per month through Cortex AI, representing massive-scale adoption even before this partnership expansion. This volume demonstrates that enterprises are moving beyond experimentation to production deployment of AI-powered data analytics.
The processing volume also validates the technical integration between Claude’s models and Snowflake’s infrastructure, proving the architecture can handle enterprise workloads at scale without performance degradation.
Customer Case Studies
Simon Data, a composable customer data platform provider, uses Claude on Snowflake to uncover previously hidden patterns and relationships in customer data while maintaining strict governance standards. The integration helps them deliver insights that were technically infeasible with manual analysis or traditional analytics tools.
Intercom, which builds AI-first customer service software, leverages Claude through Snowflake Cortex AI to power its Fin AI Agent. Dave Lynch, VP Engineering at Intercom, reports that this integration “transformed how we work with our customers to achieve increased Fin AI Agent automation rates for their support volume,” making engagements with demanding enterprise customers “holistically more efficient and more effective”.
Jake Hannan, Head of Data at Sigma, emphasizes the security advantage: “Being able to access world-class AI models, all within our trusted Snowflake environment, has been instrumental in giving our team the freedom to explore AI use cases without worrying about the safety of our data”.
Technical Integration: Where Claude Fits in Snowflake
Cross-Cloud Availability
Claude is the only frontier AI model available on all three of the world’s most prominent cloud services: Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Azure. This cross-cloud availability ensures Snowflake customers can access Claude models regardless of their underlying cloud infrastructure provider.
The integration eliminates vendor lock-in concerns and allows enterprises to maintain their existing cloud strategies while adding advanced AI capabilities. Snowflake customers can access Claude in supported regions or use cross-region inference to work with models hosted in different geographic locations.
Native SQL, Python, and REST API Access
Snowflake’s integration allows customers to access Claude using familiar SQL, Python, and REST API interfaces, dramatically simplifying adoption for existing data teams. Data engineers don’t need to learn new programming languages or frameworks; they can invoke Claude models using the same tools they use daily for data processing.
SQL interface example enables queries like:
sqlSELECT SNOWFLAKE.CORTEX.COMPLETE(
'claude-3-5-sonnet',
'Explain this customer churn pattern'
)
This native integration means AI capabilities become just another function within the Snowflake environment rather than a separate system requiring complex orchestration.
Governance and Security Features
Snowflake Horizon Catalog provides end-to-end governance and responsible AI controls, allowing teams in regulated industries to move AI agents from pilots to production with confidence. The governance framework includes data lineage tracking, access controls, audit logs, and compliance monitoring built directly into the platform.
All AI processing happens within Snowflake’s security perimeter, meaning sensitive enterprise data never leaves the governed environment. This architecture addresses one of the primary barriers to AI adoption in regulated industries: the requirement to maintain data sovereignty and compliance while leveraging advanced AI models.
Snowflake Cortex Guard provides additional protection by filtering potentially inappropriate or unsafe AI-generated responses before they reach end users.
Why This Matters for Enterprise AI Adoption
Agentic AI vs Traditional Automation
Agentic AI represents a fundamental shift from traditional automation approaches. While Robotic Process Automation (RPA) follows rigid, pre-programmed scripts, agentic AI systems can reason, plan, adapt to real-time changes, and make informed decisions when variables shift.
Key characteristics of agentic AI include autonomy (operating independently without continuous human oversight), reasoning and planning (strategizing before action), self-learning (refining actions through feedback loops), and interoperability (seamlessly integrating with multiple enterprise systems). The Snowflake-Anthropic partnership delivers these capabilities directly within enterprise data environments.
According to Gartner, nearly one-third of enterprise software solutions will integrate agentic AI capabilities by 2028, underscoring the urgency for businesses to begin this transition. This partnership positions Snowflake customers ahead of this curve with production-ready agentic AI available today.
Regulated Industries Get Production-Ready AI
Financial services, healthcare, and life sciences organizations face unique challenges deploying AI due to strict regulatory requirements. These industries require comprehensive audit trails, data governance, explainable AI outputs, and the ability to demonstrate compliance to regulators.
The Snowflake-Anthropic integration addresses these requirements by combining Claude’s ability to “show its work” with Snowflake’s built-in governance infrastructure. AI agents can explain their reasoning process, cite data sources, and provide transparency into how conclusions were reached critical capabilities for regulatory compliance.
This governance-first approach enables regulated enterprises to deploy AI agents in production environments rather than limiting them to experimental sandboxes.
The Competitive Landscape
This partnership significantly strengthens Snowflake’s position against competitors like Databricks, Google BigQuery, and Amazon Redshift in the enterprise AI market. By securing a $200 million commitment from Anthropic and integrating Claude models before competitors, Snowflake gains a differentiation advantage in the rapidly evolving AI data platform space.
Dario Amodei, CEO and Co-Founder of Anthropic, emphasized the strategic alignment: “Enterprises have spent years building secure, trusted data environments, and now they want AI that can work within those environments without compromise. This partnership brings Claude directly into Snowflake, where that data already lives”.
The joint go-to-market initiative means both companies will actively sell and support the integrated solution, providing enterprises with coordinated vendor support rather than fragmented point solutions.
Getting Started with Claude on Snowflake
Step-by-Step Implementation Guide
Existing Snowflake customers can begin using Claude models through these steps:
- Access Cortex Playground: Navigate to the AI/ML Studio tab in your Snowflake environment to test prompts and evaluate different inference configurations
- Compare Models: Use the playground to compare Claude outputs against other available models and analyze response variations with different settings
- Test Security Controls: Enable Cortex Guard to filter potentially inappropriate responses and verify governance controls meet your requirements
- Build with Familiar Interfaces: Access Claude through SQL functions, Python in Snowpark, or REST APIs using your existing development workflows
- Deploy to Production: Move validated use cases to production with built-in monitoring, governance, and observability through Snowflake Horizon Catalog
Snowflake provides a quickstart guide specifically for Claude integration to accelerate implementation. Enterprises can also visit Anthropic’s Enterprise page for additional deployment guidance and best practices.
Pricing and Licensing Considerations
The Claude integration operates on Snowflake’s consumption-based pricing model, where customers pay for actual compute and token usage rather than upfront licensing fees. This approach allows organizations to start with small pilot projects and scale based on proven ROI.
Enterprise customers should evaluate their projected token usage based on expected query volume, data complexity, and number of concurrent users. Snowflake provides cost estimation tools within the platform to help organizations forecast expenses before deployment.
Organizations already using Snowflake Cortex AI can add Claude models to their existing deployments without additional infrastructure setup or separate procurement processes.
Expert Analysis: The Future of Enterprise AI Platforms
This partnership signals a broader industry trend toward integrated AI data platforms that combine data storage, processing, governance, and AI inference in unified environments. The days of maintaining separate systems for data warehousing and AI model serving are ending as enterprises demand simplified architectures that reduce complexity and security risks.
Anthropic’s decision to invest $200 million in this partnership rather than simply licensing models to Snowflake indicates confidence that enterprise data platforms will become the primary distribution channel for frontier AI models. This approach contrasts with the consumer-focused strategies of competitors like OpenAI and emphasizes Anthropic’s commitment to enterprise markets.
The focus on agentic AI represents the next evolution beyond simple question-answering chatbots. Enterprises need AI systems that can autonomously execute multi-step workflows, make context-aware decisions, and integrate with existing business processes capabilities that require tight integration between AI models and enterprise data.
As platforms like Snowflake and Anthropic continue converging data and AI capabilities, organizations that adopt integrated architectures early will gain competitive advantages in speed to deployment, governance maturity, and operational efficiency.
Claude Integration Comparison: Snowflake vs Other Platforms
| Feature | Snowflake Cortex AI | Amazon Bedrock | Google Vertex AI | Microsoft Azure OpenAI |
|---|---|---|---|---|
| Claude Model Access | Opus 4.5, Sonnet 4.5 | Opus 4.5, Sonnet 4.5 | Opus 4.5, Sonnet 4.5 | Not available |
| Native SQL Interface | Yes | No | No | No |
| Built-in Data Governance | Snowflake Horizon | AWS IAM + custom | Google Cloud IAM + custom | Azure RBAC + custom |
| Data Movement Required | No | Yes | Yes | Yes |
| Pre-built AI Agents | Cortex Agents | Limited | Limited | Limited |
| Natural Language Analytics | Snowflake Intelligence | Requires custom build | Requires custom build | Requires custom build |
| Multimodal Analysis | Yes (text, image, audio) | Yes | Yes | Limited |
| Enterprise Support | Joint Snowflake-Anthropic | Anthropic only | Anthropic only | N/A |
Agentic AI vs Traditional Automation
| Capability | Agentic AI (Claude on Snowflake) | Traditional RPA | Standard Chatbots |
|---|---|---|---|
| Autonomy Level | High – operates independently | Low – follows scripts | Low – responds to queries |
| Reasoning Ability | Strategizes before action | Rule-based only | Pattern matching |
| Adaptability | Learns and adapts | Rigid workflows | Limited context |
| Multi-step Workflows | Yes, complex analysis | Yes, predefined only | No |
| Data Type Support | Structured + unstructured | Structured only | Mostly text |
| Governance Integration | Built-in (Snowflake Horizon) | Custom implementation | Custom implementation |
| Explainability | Shows reasoning process | Audit logs only | Limited |
| Compliance Readiness | Production-ready for regulated industries | Requires extensive custom work | Not suitable |
Snowflake-Anthropic Partnership: Advantages
For Enterprises:
- Access frontier AI models without data movement or security risks
- 90%+ accuracy on complex data queries enables production deployment
- Built-in governance meets regulatory requirements for healthcare, finance, life sciences
- Familiar SQL/Python interfaces reduce learning curve for data teams
- Cross-cloud availability (AWS, Google Cloud, Azure) prevents vendor lock-in
- Joint vendor support from both Snowflake and Anthropic
- Proven at scale with trillions of tokens processed monthly
For Data Teams:
- Natural language querying eliminates need for manual SQL writing
- Multimodal analysis across text, images, audio, and tabular data
- Pre-built AI agents accelerate time to production
- Cortex Playground enables safe testing before deployment
- No separate AI infrastructure to manage
For Business Users:
- Plain English queries replace complex BI dashboards
- Self-service analytics without technical expertise required
- Faster insights from real-time data analysis
Potential Limitations
Cost Considerations:
- Consumption-based pricing can become expensive at scale
- Token usage costs vary based on model choice (Opus vs Sonnet)
- Requires existing Snowflake subscription and infrastructure
Technical Requirements:
- Limited to Snowflake customers; not available as standalone offering
- Cross-region inference may have latency implications
- Organizations must already have data in Snowflake to benefit
Adoption Challenges:
- Change management needed for teams accustomed to traditional BI tools
- Prompt engineering skills helpful for optimal results
- Initial setup requires understanding of Cortex AI architecture
Competitive Landscape:
- Other LLMs (GPT-4, Gemini) also available in Cortex, creating model choice complexity
- Rapid AI evolution may require frequent updates to stay current
Snowflake Cortex AI with Claude: Technical Specifications
Supported Claude Models:
- Claude Opus 4.5 (frontier performance, coding, agents, computer use)
- Claude Sonnet 4.5 (enterprise intelligence, natural language querying)
Access Methods:
- SQL functions (SNOWFLAKE.CORTEX.COMPLETE)
- Python via Snowpark
- REST APIs (snowflakecomputing.com/api/v2/cortex/inference:complete)
- Cortex Playground (no-code interface in AI/ML Studio)
Cloud Platform Support:
- Amazon Bedrock
- Google Cloud Vertex AI
- Microsoft Azure
Data Type Capabilities:
- Structured data (tabular, relational databases)
- Unstructured text (documents, logs, transcripts)
- Images
- Audio files
Performance Benchmarks:
- 90% accuracy on complex text-to-SQL tasks
- Trillions of tokens processed monthly across customer base
- Context window: Extensive (model-dependent)
Security & Governance:
- All processing within Snowflake security perimeter
- Snowflake Horizon Catalog for end-to-end governance
- Cortex Guard for content filtering
- Built-in audit logging and compliance monitoring
- Data lineage tracking
- Role-based access controls
Geographic Availability:
- Supported in Snowflake regions with Cortex AI
- Cross-region inference enabled for non-supported regions
Integration Points:
- Snowflake Intelligence (enterprise intelligence agent)
- Snowflake Cortex AI Functions
- Snowflake Cortex Agents (custom agent builder)
- Snowflake Copilot (AI assistant for analysts)
Pricing Model:
- Consumption-based (pay per token/compute usage)
- No separate licensing fees beyond Snowflake subscription
- Costs vary by model (Opus vs Sonnet) and usage volume
Compatibility Requirements:
- Active Snowflake account
- Access to Cortex AI (availability varies by region)
- Appropriate role permissions within Snowflake
Frequently Asked Questions About Snowflake-Anthropic Partnership
When was the Snowflake-Anthropic partnership announced?
Snowflake and Anthropic announced the expanded $200 million partnership on December 3, 2025. While the companies had been working together since Claude 3.5 Sonnet became available in Cortex AI in January 2025, this announcement formalizes a deeper strategic alignment with joint go-to-market initiatives and co-innovation commitments.
How much does it cost to use Claude on Snowflake?
Claude on Snowflake operates on a consumption-based pricing model where customers pay for actual compute usage and tokens processed rather than upfront licensing fees. Costs vary based on which Claude model you use (Opus 4.5 vs Sonnet 4.5), query complexity, and processing volume. Snowflake provides cost estimation tools within the platform to help forecast expenses before deployment.
What is the difference between Snowflake Intelligence and Snowflake Cortex AI?
Snowflake Cortex AI is the underlying platform that provides access to large language models, AI functions, and agent-building capabilities. Snowflake Intelligence is a specific enterprise intelligence agent built on Cortex AI that uses Claude Sonnet 4.5 to answer natural language questions across structured and unstructured data. Think of Cortex AI as the infrastructure and Snowflake Intelligence as a pre-built application running on that infrastructure.
Can I use Claude on Snowflake if my data is on AWS/Google Cloud/Azure?
Yes, Claude is available on Snowflake across all three major cloud providers: Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Azure. This cross-cloud availability ensures you can access Claude models regardless of your underlying cloud infrastructure, though you do need an active Snowflake subscription.
How does Claude on Snowflake maintain data security and compliance?
All Claude processing happens within Snowflake’s security perimeter, meaning your data never leaves the governed environment. Snowflake Horizon Catalog provides end-to-end governance with data lineage tracking, access controls, audit logs, and compliance monitoring. Cortex Guard adds content filtering to block inappropriate AI-generated responses. This architecture enables regulated industries like healthcare and finance to deploy AI agents in production while maintaining compliance.
What industries benefit most from the Snowflake-Anthropic integration?
Financial services, healthcare, and life sciences organizations gain the most immediate value due to strict regulatory requirements that demand governed AI with audit trails and explainability. However, any industry working with large volumes of structured and unstructured data can benefit, including retail (customer analytics), manufacturing (supply chain optimization), and technology (product analytics).
How accurate is Claude compared to other AI models on Snowflake?
Claude achieves greater than 90% accuracy on complex text-to-SQL tasks according to Snowflake’s internal benchmarks. Arun Agarwal, Lead Product Marketing Manager for Cortex AI at Snowflake, specifically highlighted Claude 3.5 Sonnet’s “advanced reasoning capabilities, strong knowledge retention, and high coding proficiency” as factors that set it apart from competing models.
Can I build custom AI agents with Claude on Snowflake?
Yes, Snowflake Cortex Agents enables customers to build production-ready custom data agents powered by Claude that retrieve and reason over both structured and unstructured data. These agents can execute multi-step analysis, show their reasoning process, and maintain context across complex workflows. Unlike simple chatbots, Cortex Agents can autonomously determine what data is needed, pull it from appropriate sources, and deliver comprehensive answers.
Featured Snippet Boxes
What is the Snowflake-Anthropic partnership?
The Snowflake-Anthropic partnership is a $200 million, multi-year agreement announced December 3, 2025, that integrates Claude AI models into Snowflake Cortex AI and Snowflake Intelligence, enabling 12,600+ enterprises to query structured and unstructured data using natural language while maintaining rigorous governance and security standards.
What is Snowflake Cortex AI?
Snowflake Cortex AI is a fully managed AI and machine learning platform built directly into the Snowflake Data Cloud that enables teams to run large language models, build AI-powered applications, and analyze unstructured data without moving data outside Snowflake’s governed environment. It provides access to industry-leading models through familiar SQL, Python, and REST API interfaces.
What is agentic AI?
Agentic AI refers to artificial intelligence systems capable of autonomous decision-making, reasoning, planning, and executing multi-step workflows without continuous human oversight. Unlike traditional automation that follows rigid scripts, agentic AI adapts to real-time changes, learns from feedback loops, and integrates seamlessly with multiple enterprise systems.
How accurate is Claude on Snowflake?
Claude achieves greater than 90% accuracy on complex text-to-SQL tasks according to Snowflake’s internal benchmarks. This high accuracy enables enterprises to deploy Claude-powered AI agents in production environments for critical business analysis and decision-making workflows.
Which Claude models are available on Snowflake?
Snowflake Cortex AI provides access to Claude Opus 4.5 and Claude Sonnet 4.5. Claude Sonnet 4.5 powers Snowflake Intelligence for natural language querying, while Claude Opus 4.5 delivers frontier performance for coding, autonomous agents, and multimodal analysis across text, images, and audio.
How do enterprises access Claude on Snowflake?
Enterprises access Claude models on Snowflake through native SQL functions, Python in Snowpark, REST APIs, or the Cortex Playground interface in AI/ML Studio. All access occurs within Snowflake’s security perimeter without requiring data movement or separate AI infrastructure.
