Tsubasa Kanno

Posted on Jul 7

Game-Changing UI Updates Make Snowflake Cortex Search Management Effortless

#snowflake #vectordatabase #nlp #rag

Introduction

As we progress through 2025, Snowflake's AI capabilities (Cortex AI) continue to expand dramatically. Snowflake AI & ML Studio has undergone frequent updates, making numerous AI/ML features accessible through intuitive UI interfaces. This evolution truly embodies Snowflake's commitment to usability and simplicity.

Today I'm excited to share major improvements to Cortex Search management UI within Snowflake AI & ML Studio! While Cortex Search service management was traditionally centered around SQL commands, we can now perform comprehensive management through GUI interfaces. Everything from service overviews and configuration changes to data previews and playground functionality can now be completed entirely within Snowsight.

This transformation enables everyone from data engineers to AI application developers to leverage Cortex Search more efficiently. I'll walk through these new management UI capabilities with actual screenshots, demonstrating their value and practical usage.

Understanding Cortex Search

Let me briefly explain what Cortex Search is for those new to the technology. Cortex Search is a fully-managed enterprise search service provided by Snowflake.

Key Features

Hybrid Search: Combines vector search (semantic similarity) with keyword search (lexical similarity) for high-precision results
Automatic Embedding Generation: Automatically and regularly vectorizes text data to enable semantic search capabilities
Fully Managed: No infrastructure management or tuning required - ready to use immediately
Snowflake Native: Complete integration with Snowflake's data governance and security features

For detailed usage and implementation examples, check out my previous articles: "Snowflake Cortex Search for RAG Chat Applications" and "Enhancing RAG Applications with Cortex Search Boosts & Decays".

Note (2025/7/7): Snowflake AI & ML Studio is currently in public preview, so features may undergo significant updates. However, Cortex Search itself is already Generally Available!

Note: This article represents my personal views and not those of Snowflake.

Cortex Search Management in Snowflake AI & ML Studio

Snowflake AI & ML Studio serves as Snowflake's GUI-based AI/ML environment, and Cortex Search creation capabilities have been available for some time. Recent updates have significantly enhanced Cortex Search management functionality, allowing nearly all tasks necessary for Cortex Search creation and operation to be completed entirely within Snowflake AI & ML Studio.

Accessing AI & ML Studio

First, log into Snowsight and click AI & ML → Studio from the left navigation pane.

Within Studio, you can manage various AI/ML features including Cortex Search, Cortex Analyst, LLM Playground, and ML function creation through web-based UI.

Revolutionary Cortex Search Management UI

Note: Since Cortex Search creation screens remain unchanged from previous versions, I'll focus on the management improvements here.

1. Cortex Search Service Overview

When you select Cortex Search from AI & ML Studio, all existing Cortex Search services are displayed in a comprehensive list view.

Information visible at a glance:

Service names and status indicators
Database and schema information
Index creation status
Index refresh frequency

Executable operations:

Create new services (Create button)
View detailed service information
Test searches in playground environment
Manually trigger index updates
Modify index refresh frequency and warehouse settings
Pause/resume index creation
Pause/resume services
Delete services

Previously, information like this was only accessible through SQL commands such as SHOW CORTEX SEARCH SERVICES;. Now it's presented in a visually intuitive format. This is particularly valuable since Cortex Search consumes computing resources during index creation - helping avoid situations like "Oops, I've been updating an unused Cortex Search service forever!"

2. Service Details and Data Preview

Selecting a specific Cortex Search service reveals detailed configuration information, actual data previews, and Cortex Search cost information.

Detailed information displayed:

Search target column specifications
Attribute column details
Last update timestamps
Warehouse utilization
Embedding model configurations
Service query URLs and sample code for Python/API calls
Actual data preview displays
Cortex Search cost analytics

What's particularly noteworthy is the ability to examine actual vector data. While most managed services typically hide this information, being able to inspect the actual embedded vector data provides incredibly valuable debugging information for AI engineers.

3. Playground Functionality

One of the most exciting features is the playground functionality, which allows you to test searches in real-time.

Playground capabilities:

Execute natural language search queries
Display search result chunks
Apply attribute-based filtering
Verify Boosts & Decays effects

This empowers developers to validate search quality before implementation.

Business Value and Impact

Dramatic Development and Operations Efficiency Gains

Traditional Challenge	New Management UI Solution
Required memorizing and executing SQL commands	Intuitive GUI operations
Difficult to understand service status	Real-time status displays and dashboards
Time-consuming search quality verification	Instant testing via playground
Challenging to obtain debugging information	Vector data visualization
Risk of configuration errors	GUI-guided setup

Enhanced ROI

Development Time Reduction:

Decreased service management time
Reduced search quality testing and validation time

Operational Cost Optimization:

Real-time monitoring through GUI enables appropriate resource management
Pre-testing in playground reduces trial-and-error in production environments
Eliminated costs from configuration error-induced recreations

Democratizing AI Application Development

Cortex Search management, which previously required SQL expertise, has become more accessible through GUI interfaces. This enables:

Business users to verify search quality and make basic configuration changes
Application developers to more easily integrate enterprise search and RAG chat applications

Conclusion

The Cortex Search management UI revolution in Snowflake AI & ML Studio has dramatically lowered barriers for enterprise search utilization and RAG chat application development. Operations that previously required SQL expertise can now be performed through GUI, and the playground functionality makes search quality verification simple and straightforward.

Key value propositions include:

Massive development efficiency gains: Significant time savings through intuitive GUI operations
Quality improvements: Enhanced production search quality through playground pre-testing
Reduced learning costs: New engineers can leverage Cortex Search capabilities in minimal time
Strengthened governance: Unified management within Snowflake's integrated environment maintains security and governance
Enhanced visibility: Comprehensive information visualization including vector data

For anyone considering RAG application development or enterprise search system implementation, I highly recommend exploring these new management UI capabilities. Snowflake's AI functionality continues evolving as the "AI platform for enterprise data" - advancing both usability and functionality.