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Overview

Snowflake Cortex brings AI capabilities directly to your data warehouse, allowing you to run LLMs and embedding models on your data without moving it outside your secure environment. This setup leverages your existing CloudLink connection to access Snowflake’s AI capabilities.
Prerequisites: You must have a CloudLink connection configured with key-pair authentication to access Snowflake Cortex AI features.
Authentication Requirement: Snowflake Cortex AI features are only available when using key-pair authentication. Password authentication cannot access these capabilities.
Before setting up Snowflake Cortex, ensure your CloudLink is properly configured:
  1. Navigate to CloudLink Settings
    • Go to Organization Settings → Cloud Credentials
    • Verify your Snowflake connection is active
  2. Confirm Key-Pair Authentication
    • Your CloudLink must use key-pair authentication
    • If using password authentication, you’ll need to upgrade to key-pair

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Verify Snowflake Account Access

Your Snowflake account must have access to Cortex AI features:

Account Requirements

Snowflake Edition: Enterprise or higherCortex Features: Available in most regionsPermissions: USAGE privileges on Cortex functions

Region Availability

Supported Regions: Most AWS, Azure, and GCP regionsModel Access: Varies by region and account typeBilling: Cortex usage billed through Snowflake

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Step 2: Enable Snowflake Cortex in Elementum

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Automatic Discovery

When you have a CloudLink connection with key-pair authentication, Elementum automatically discovers available Snowflake Cortex capabilities:
1

Navigate to Providers

In Organization Settings, go to the Providers tab
2

Create Snowflake Provider

Click ”+ Provider” and select SnowflakeYou’ll see your existing CloudLink connections listed
3

Configure Provider

Provider Name: Enter a descriptive name (e.g., “Snowflake Cortex AI”)CloudLink: Select your key-pair authenticated CloudLinkService Account Credentials: Auto-populated from your CloudLink
4

Save and Test

Click “Save” to create the providerElementum will test the connection and discover available models

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Manual Configuration

If automatic discovery doesn’t work:
Provider Name: Descriptive name for your Snowflake providerLocation: Your Snowflake region and account detailsProject ID: Your Snowflake account identifierCloudLink: Select the appropriate CloudLink connection

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Step 3: Available Snowflake Cortex Models

Once configured, you’ll have access to various AI models through Snowflake Cortex:

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Language Models (LLMs)

ModelPrimary Use CaseSpeedIntelligenceBest For
Claude Sonnet 4Advanced reasoning and analysis⭐⭐⭐⭐⭐⭐⭐⭐Complex problem-solving, detailed analysis, premium applications
Claude 3.7 SonnetCost-effective reasoning⭐⭐⭐⭐⭐⭐⭐⭐Daily tasks, customer support, balanced performance
Claude Opus 4Most complex reasoning⭐⭐⭐⭐⭐⭐⭐Extremely complex tasks, research, advanced analysis (expensive)
Mistral Large 2European AI compliance⭐⭐⭐⭐⭐⭐⭐European regulations, multilingual tasks
Model Recommendations: Use Claude 3.7 Sonnet for most daily tasks and cost-effective operations. Choose Claude Sonnet 4 for advanced reasoning and premium applications. Reserve Claude Opus 4 for the most complex tasks that require maximum intelligence (note: very expensive).

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Embedding Models

ModelPrimary Use CaseSpeedQualityBest For
Snowflake Arctic L V2.0Latest high-quality embeddings⭐⭐⭐⭐⭐⭐⭐⭐⭐Modern search applications, premium AI Search
Snowflake Arctic L V1.5Reliable embeddings⭐⭐⭐⭐⭐⭐⭐⭐Stable search applications, production use
Embedding Recommendations: Use Snowflake Arctic L V2.0 for new implementations and highest quality search results. Arctic L V1.5 provides reliable performance for production workloads.
Model Availability: Available models depend on your Snowflake account tier, region, and current Cortex offerings. Model selection may vary over time.

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Step 4: Create AI Services

With Snowflake Cortex configured, create AI Services to use the models:
1

Navigate to Services

In Organization Settings, go to the Services tab
2

Create LLM Service

Click ”+ Service” and select from available Snowflake modelsService Name: Descriptive name (e.g., “Snowflake Claude 3.5”)Model: Select from discovered Cortex modelsCost Tracking: Set cost per million tokens (optional)
3

Create Embedding Service

For AI Search capabilities, create an embedding serviceService Name: Descriptive name (e.g., “Snowflake Embeddings”)Model: Select an embedding modelConfiguration: Additional settings for embedding behavior
4

Test Services

Use the built-in testing interface to verify services work correctly

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Benefits of Snowflake Cortex

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Data Security and Privacy

Data Residency

No Data Movement: AI runs directly on your data warehouseCompliance: Maintains data governance and complianceSecurity: Leverages Snowflake’s security modelPrivacy: Your data never leaves your environment

Performance

Direct Access: No data transfer latencyScalability: Leverages Snowflake’s compute powerOptimization: Models optimized for structured dataCost Efficiency: Reduces data movement costs

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Integration Advantages

  1. Seamless Data Access: AI models can directly query your tables
  2. Real-Time Processing: Process data as it arrives
  3. Unified Platform: Single environment for data and AI
  4. Cost Optimization: Leverage existing Snowflake infrastructure

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Configuration Best Practices

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Performance Optimization

Model Complexity: Larger models may require bigger warehousesConcurrent Usage: Scale warehouses based on simultaneous requestsCost Balance: Balance performance needs with compute costsAuto-Scaling: Enable auto-scaling for variable workloads

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Cost Management

Monitor Usage

Cortex Billing: Monitor AI function usage in SnowflakeCompute Costs: Track warehouse usage for AI workloadsData Transfer: Minimize unnecessary data movementOptimization: Regularly review and optimize usage patterns

Efficiency Tips

Batch Processing: Process multiple requests togetherCaching: Cache frequent AI resultsModel Selection: Choose appropriate models for tasksQuery Optimization: Optimize SQL queries using AI functions

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Troubleshooting

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Advanced Configuration

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Custom Model Access

For specialized or private models:
  1. Model Registration: Register custom models in Snowflake
  2. Access Control: Configure proper permissions
  3. Performance Tuning: Optimize for your specific use case
  4. Monitoring: Set up custom monitoring and alerting

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Multi-Region Setup

For global deployments:
  1. Region Selection: Choose regions closest to your data
  2. Data Replication: Consider data residency requirements
  3. Failover: Implement failover strategies
  4. Compliance: Ensure regional compliance requirements

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Next Steps

With Snowflake Cortex configured:

Create AI Services

Set up specific LLM and embedding services using Cortex models

Enable AI Search

Use Snowflake embeddings for intelligent search on your data

Build Agents

Create agents that can directly access your Snowflake data

Optimize Performance

Configure warehouses for optimal AI performance
Snowflake Cortex provides secure, high-performance AI capabilities directly on your data warehouse. This approach ensures data privacy while delivering advanced AI features for your workflows.