Use Case
Unstructured Data Analytics
Efficiently extract insights by analyzing documents, images and audio at scale with Snowflake Cortex AI's SQL-powered pipelines, multimodal functions and industry-leading LLMs — all within the secure Snowflake perimeter.
Overview
Unstructured data holds a treasure trove of value — but it can be hard to unlock. Uncover insights for all data types with AI-powered analytics from Snowflake.
Sprawling data can be difficult to analyze, leading to information gaps that can impact business decisions. Get meaningful insights without required data movement by unifying your analytics across structured and unstructured data.
Use AI-powered SQL and a no-code interface to easily perform generative AI tasks
Multimodal data processing and efficient unstructured data analytics — no setup required.
Fully managed infrastructure optimized for performance
Use SQL functions to build gen AI apps with performant inference, eliminating the need for infrastructure management and scaling.
Integrated governance and observability for data and AI
Protect your data used in gen AI applications with Snowflake's unified security, governance and data access controls. Reduce harmful content with built-in guardrails.
Easily analyze data
Query and analyze multimodal data using an intuitive, AI-powered SQL
- Use Cortex AISQL to analyze your full data ecosystem, including text, images and structured data. Summarize, extract and join with industry-leading LLMs.
Securely gain actionable insights
Transform unstructured data into actionable insights at scale with batch LLM inference in Snowflake
Analyze text, images and documents with Cortex AI’s batch LLM inference.
Process multimodal data directly in Snowflake.
Industry-leading models and optimized pipelines deliver fast, more cost-efficient AI workloads.
Gain end-to-end AI observability
Enterprise-grade observability, governance and security
Securely process unstructured data at scale using Snowflake’s row- and column-level controls, providing granular governance.
Monitor response quality using end-to-end LLM evaluations and observability.
Get Started
Take the next stepwith Snowflake
Start your 30-day free Snowflake trial today
- $400 in free usage to start
- Immediate access to the AI Data Cloud
- Enable your most critical data workloads
Unstructured Data in Snowflake
Frequently Asked Questions
Explore how Snowflake helps you unlock insights from unstructured data using powerful AI/ML features. This FAQ covers key capabilities, data types and model governance.
Snowflake allows you to store unstructured data (like PDFs, images, audio, video) in stages or using Directory Tables. You can then analyze it directly using Snowflake Cortex AI capabilities, such as Document AI, to extract information from documents using pre-trained models via SQL, while the Cortex COMPLETE Multimodal function allows direct analysis of images. You can also use Snowpark for Python, Java or Scala. Write custom code (UDFs and Stored Procedures) using libraries for OCR, NLP, image processing, etc., to process and analyze unstructured data where it resides, bringing the computation to the data.
Yes! Snowflake enables this through its AI capabilities, such as Snowflake Cortex Search, which allows you to build retrieval augmented generation (RAG) applications to find information and "chat" with your documents by asking questions in natural language. You can also use Cortex LLM Functions and build custom applications that use LLMs to understand natural language queries and extract insights or generate responses based on the content of your unstructured data (once processed or indexed).
Snowflake Document AI is specifically designed to extract data from various document formats, including PDFs (text-based and scanned), and can also handle content like handwritten text, logos and checkboxes within these documents. Snowflake Cortex's powerful multi-modal capabilities allow you to directly process and analyze image files within Snowflake. While raw audio/video analysis might require preprocessing (e.g., using Snowpark for transcription or feature extraction), the extracted text or metadata can then be analyzed using Cortex AI functions.
Yes, Snowflake allows you to control access to specific AI models available through Snowflake Cortex. This is managed via a model allowlist at the account level and through more granular role-based access control (RBAC) by granting or revoking privileges to specific model objects to defined user roles.
Customer data is not used to train, re-train or fine-tune AI models made available to other Snowflake customers. If you choose to fine-tune a model using your data within Snowflake, that fine-tuned model is available exclusively for your use and is not provided to any third-party model developer or other customers.
When you use pre-trained foundation models offered through Snowflake Cortex, multiple customers are accessing the same underlying base model version provided and managed by Snowflake (or its third-party partners). However, your specific data, prompts and outputs remain isolated to your account and are not visible to or mixed with other customers' data. Snowflake enables data privacy and security within its multi-tenant architecture.
