What are the AI Features in Snowflake?

Quick answer

Snowflake delivers powerful AI through its Cortex platform and AI Data Cloud. The platform provides fully managed AI services that use large language models to parse unstructured data, answer questions, and provide smart help. Features include natural language querying, document processing, and automated insights—all within your governed data space.

Major updates in late 2025 brought Snowflake Intelligence, Cortex Agents, and seven Cortex AI Functions to general availability. The platform added OpenAI GPT-5.2 access, multimodal support for text and images, and AI_REDACT for automated PII protection. These tools open AI access to business users while keeping enterprise-grade security and governance controls in place.

Does Snowflake have an AI agent?

Yes. Snowflake supports AI agents through multiple offerings.

Snowflake Intelligence enables users to build ‘data agents’ that answer questions about structured and unstructured data, plus take action across third-party platforms like Salesforce and Google Workspace. These agents leverage Snowflake’s Cortex platform for advanced data analysis and automated workflows.

Cortex Agents, now generally available since November 2025, orchestrate across both structured and unstructured data sources. They plan tasks, use tools to execute them, and generate responses. Agents use Cortex Analyst for structured data and Cortex Search for unstructured data, along with LLMs, to analyze information.

The Data Science Agent automates repetitive machine learning tasks like data prep, feature engineering, and model training. This cuts manual effort and speeds AI projects without giving up quality or control.

For more information, visit the official Snowflake Intelligence announcement.

What are the latest Snowflake AI features?

AI_REDACT for PII protection (December 2025 – GA)

AI_REDACT detects and removes personally identifiable information from unstructured text using a large language model. The function recognizes categories like names and addresses, including partial PII like first or last names, and replaces them with placeholders.

This addresses a major enterprise concern: keeping sensitive data safe while still using it for AI analysis. Teams can now process documents at scale without manual review for PII.

OpenAI GPT-5.2 on Cortex AI (December 2025)

OpenAI’s latest models are now available on Snowflake Cortex AI. Users can access GPT-5.2 through LLM functions and REST APIs while keeping data secure within Snowflake’s governed environment.

Cortex AI Functions (November 2025 – GA)

Snowflake announced general availability of Cortex AI Functions in November 2025. These deliver production-ready AI within the Snowflake SQL engine.

Four functions moved from preview to GA:

• AI_CLASSIFY: Sorts text or image inputs into user-defined categories based on plain-language definitions
• AI_TRANSCRIBE: Transcribes audio and video files, pulling text, timestamps, and speaker info
• AI_EMBED: Generates embedding vectors for text or image inputs for similarity search, clustering, and classification
• AI_SIMILARITY: Calculates embedding similarity between two inputs without creating explicit vectors

These join three functions already in GA:

• AI_TRANSLATE: Converts text between languages using state-of-the-art language models
• AI_EXTRACT: Pulls information from text, documents, and images based on user instructions
• AI_SENTIMENT: Analyzes overall and category sentiment in text

With AI Functions, you can build scalable, multimodal AI pipelines that run entirely inside Snowflake. Text, image, audio, and video intelligence happen without external services or data movement.

AI_COMPLETE function (November 2025 – GA)

The AI_COMPLETE function reached general availability, giving developers direct access to LLM completions within SQL queries. This enables custom prompts and flexible AI interactions without leaving the Snowflake environment.

Hugging Face model imports (November 2025 – Preview)

Snowflake now allows importing models from Hugging Face directly into the platform. This preview feature expands the range of AI models available to data scientists and engineers working within Snowflake.

Snowflake Intelligence (November 2025 – GA)

Snowflake Intelligence is a unified platform for building ‘data agents’ using Snowflake-hosted business intelligence data and third-party platform connections. These agents provide instant answers to business questions and execute actions across integrated tools.

The platform goes beyond simple Q&A. Once insights surface, users can ask the same agent to act on them across third-party tools—from creating forms in Google Workspace to modifying Salesforce CRM entries.

Cortex Agents (November 2025 – GA)

Cortex Agents orchestrate across structured and unstructured data sources to deliver insights. They work through three key capabilities:

• Planning: Parse requests to orchestrate a plan. They explore options, split tasks into subtasks, and route across tools while ensuring governed access
• Tool use: Retrieve data using Cortex Search for unstructured sources and Cortex Analyst for structured data
• Reflection: Evaluate results after each tool use to determine next steps—asking for clarification, iterating, or generating a final response

Snowflake Openflow (November 2025 – GA)

Openflow automates data ingestion and integration from varied sources—including unstructured data—to unify enterprise data within Snowflake’s data lakehouse. The managed, cloud-native implementation of Apache NiFi provides visual drag-and-drop data flow creation.

Key use cases include:

Ingesting unstructured data from sources like Google Drive and SharePoint for AI assistants

Change data capture from relational databases into Snowflake

Real-time event ingestion from streaming services like Apache Kafka

What are the popular Snowflake AI features?

Snowflake Cortex Document AI

Transform how you handle unstructured data. Cortex Document AI enables SQL users to parse, extract, and summarize structured data from unstructured files including PDFs, images, and audio using large language models and built-in NLP.

Everything happens within Snowsight’s interface. No special coding required. This opens advanced document processing to business users who need quick insights from complex files.

The AI spots key information, extracts relevant data points, and summarizes lengthy documents. Perfect for processing contracts, reports, or research papers at scale.

Availability: Generally available to accounts in AWS, Azure, and GCP commercial regions. Usage incurs compute charges based on document size and LLM processing needs.

Snowflake Copilot

Your SQL writing assistant. Copilot helps SQL developers speed development from inside the Snowflake UI by turning text into SQL. Describe what you want in natural language, and Copilot generates optimized queries.

The tool explains existing queries, suggests improvements, and helps debug complex SQL. This cuts development time and makes advanced analytics accessible to users with varying SQL skills.

Availability: Included in Enterprise and Business-Critical plans. Extended features available as add-ons, with LLM queries counting against compute quotas.

Universal Semantic Search

Find anything, fast. Cortex Search is a fully managed search solution that indexes and queries unstructured data and documents. The system uses vector indexing and retrieval-augmented generation models.

Users discover assets like tables, dashboards, and documents through conversational queries. Instead of remembering exact names or locations, ask “show me sales data from last quarter” and get relevant results instantly.

Availability: Available to all paid Snowflake accounts. Performance scales with warehouse size and usage.

Snowpark Container Services

Deploy custom AI workloads directly in Snowflake. Snowpark Container Services is a fully managed container offering for custom ML/AI workloads, including GPU-powered LLMs.

This ensures data privacy and sovereignty. Your models run where your data lives, removing the need to move sensitive information to external AI services.

Availability: Available in Enterprise plans with compute billed based on container runtime and resource allocation.

Distributed hyperparameter optimization

Speed machine learning at scale. The platform supports distributed tuning including GridSearchCV and RandomSearchCV across Snowflake’s compute cluster. This cuts model development time from days to hours.

The system parallelizes optimization tasks and manages resource allocation automatically. Data scientists can experiment with more model configs without long wait times.

Availability: Advanced ML features enabled on Enterprise and Business-Critical plans. Model training billed per compute usage.

Common limitations of Snowflake AI

Pricing complexity and compute costs

The biggest challenge? Unexpected expenses. Pay-as-you-go pricing based on warehouse size and compute hours can result in surprise costs—especially for LLM experiments and high-frequency agent use.

Forum discussions emphasize careful cost management and query optimization to avoid budget overruns. AI workloads intensify this challenge. Snowflake Cortex incurs costs in unique ways beyond standard compute, storage, and data transfer.

The rapid advancement of AI features requires massive investments in GPU clusters. As Snowflake provides more compute-heavy AI services, costs may rise if efficiency gains don’t keep pace.

Throttling and API constraints

Performance can suffer during peak usage. AI/LLM requests may be throttled during high usage periods, resulting in delayed processing. These limits provide fair access to all customers.

Throttled requests return errors and require manual retries. This impacts time-sensitive AI applications where consistent response times matter.

Governance and accuracy requirements

Enterprise AI demands precise, measurable accuracy. Business-critical applications need exact answers, not probabilistic ones. Questions like “How much revenue did we generate yesterday?” require verified responses.

According to an MIT Technology Review Insights study with Snowflake, 59% of respondents cite governance, privacy, and security as top challenges in deploying AI. Organizations will increasingly insist on systematic methods to measure agent accuracy before deploying at scale.

Session management and integration challenges

Native connectors sometimes struggle with session consistency. Users report issues with data handling for large queries, especially in Power BI integrations. Extra gateways or custom code often become necessary for reliable data streaming.

Compatibility requirements aren’t always clear in advance, leading to unexpected delays.

Feature limitations in specialized use cases

Features like database mirroring support only simple table pass-through with no support for dynamic tables or view-based transformations. Advanced transformation must happen upstream, which can limit integration effectiveness.

Composite keys aren’t supported for exports. Export features support single tables only—no joined queries. These constraints affect teams expecting full ELT capabilities within Snowflake’s ecosystem.

Skills gap and expertise requirements

Security, cost, and shortage of skills rank among primary concerns for organizations starting AI work. The enterprise AI mindset starts with data rather than copilots and LLMs. Unless organizations are convinced about security, they won’t put anything in production.

Complex authentication setup across different access methods requires technical expertise. Managing OAuth, key pairs, SAML, and SSO configurations demands careful credential management across environments.

What are the alternatives to Snowflake AI?

Coefficient AI

Skip the complex setup. Coefficient’s AI Sheets Assistant transforms Google Sheets into a powerful analytics platform using natural language commands.

• Dashboard automation: Build comprehensive dashboards with charts, metrics, and insights automatically. The AI analyzes your data structure and creates appropriate visualizations without manual configuration.
• Formula intelligence: Generate, fix, and explain complex formulas through conversational prompts. No need to remember VLOOKUP syntax or debug broken calculations—just describe what you want.

Unlike Snowflake’s enterprise-focused approach, Coefficient works directly in the spreadsheets teams already use. You get AI-powered insights without migrating data or learning new platforms. Perfect for teams who need quick analytics without the overhead of data warehouse management.

Zapier

Connect AI across your entire workflow. Zapier’s AI features automate repetitive tasks between thousands of apps without coding.

• Intelligent automation: Set up workflows that trigger based on AI analysis of incoming data. For example, automatically categorize support tickets and route them to the right team based on sentiment analysis.
• Natural language processing: Extract insights from text across different platforms and trigger actions based on the results. Process customer feedback, social media mentions, or survey responses and automatically update your CRM or project management tools.

Clay

Supercharge your data research with AI-powered enrichment. Clay combines web scraping, data enrichment, and AI analysis in a single platform.

• Smart data discovery: Use AI to find and verify contact information, company details, and other business intelligence from across the web. The platform automatically cross-references multiple sources for accuracy.
• Personalization at scale: Generate customized outreach messages, analyze company websites for relevant talking points, and score leads based on AI analysis of multiple data points.

Clay excels at turning raw prospect lists into actionable intelligence, making it ideal for sales and marketing teams who need comprehensive contact research.

Get started with AI-powered analytics

The AI revolution in data analytics is here. But you don’t need complex infrastructure to benefit.

Snowflake offers enterprise-grade AI capabilities for organizations with sophisticated data warehouse needs. The platform excels when you’re processing massive datasets and need advanced AI features within a governed environment.

For teams seeking immediate AI assistance with existing spreadsheet workflows, Coefficient provides a simpler path. Transform your Google Sheets into intelligent dashboards and automated analysis tools without the learning curve or infrastructure investment.

The choice depends on your scale and complexity requirements. Large enterprises benefit from Snowflake’s comprehensive AI Data Cloud. Smaller teams and departments often find faster value with Coefficient’s spreadsheet-native approach.

Ready to see how AI can accelerate your analytics? Start building intelligent spreadsheets today.

FAQs

What AI capabilities does Snowflake have?

Snowflake offers two broad categories of AI features: Snowflake Cortex for understanding unstructured data and providing intelligent assistance, and Snowflake ML for building custom models. The platform includes natural language querying, document processing, and automated insights. Coefficient provides similar AI capabilities directly in Google Sheets, making advanced analytics accessible without complex data warehouse setup.

How to use OpenAI in Snowflake?

Snowflake Cortex AI provides serverless access to foundation models and includes LLM functions for text analysis. You can access these through SQL functions and the Cortex platform. For spreadsheet users, Coefficient offers integrated OpenAI functionality through GPTX functions, enabling text analysis and content generation directly in your existing workflows.

What are the features of Snowflake?

Snowflake features include separated storage and compute layers, just-in-time provisioning, automatic scaling, zero-copy cloning, and secure data sharing. The AI features add natural language processing, automated insights, and intelligent assistance on top of these core capabilities. Teams working primarily in spreadsheets can access similar automation and intelligence through Coefficient’s AI assistant.

What is Snowflake AI Cortex?

Snowflake Cortex is a suite of AI features that use large language models to understand unstructured data, answer questions, and provide intelligent assistance—all within the governed Snowflake environment. It includes document processing, natural language querying, and automated analysis capabilities. For spreadsheet-based workflows, Coefficient’s AI provides comparable functionality with charts, formulas, and dashboard creation through natural language commands.