Netflix
DO MOREWITH SNOWFLAKE
From ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications, Snowflake helps you innovate faster and do more with your data.
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Your Snowflake Team



Use cases
Turn data into intelligence with AI
Data Agents
Unstructured Data Analytics
ML Workflows
Pipeline Lifecycle
Ingestion
Talk with your data
Build agents and conversational apps grounded in enterprise data
Get accurate answers to your business questions with an easy-to-use, intuitive interface.
Efficiently build data agents for document analysis, multimodal data processing and contextual information synthesis.
- Access all your enterprise data — both structured and unstructured — with scalable and reliable retrieval powered by Cortex Analyst and Cortex Search.
Efficiently process text and multimodal data at scale
Analyze batch data within Snowflake’s secure perimeter
Streamline ML development and production
Accelerate end-to-end machine learning workflows
Develop, deploy and monitor ML features and models at scale with a fully integrated platform that brings together tools, workflows and compute infrastructure to the data.
Develop models faster with Notebooks using a container-based runtime that distributes data loading and model training on GPUs.
Serve models trained anywhere for inference with Snowflake Model Registry.
Enable reliable data movement
Build, deploy and optimize data pipelines faster
- Streamline the entire pipeline lifecycle and quickly adopt new data engineering practices — or merge with existing workflows.
- Democratize data engineering with Snowflake’s end-to-end workflows, which include a growing set of native capabilities and tight integrations with open standards and data engineering-specific tools.

Connect from any source
Handle data ingestion built for AI and interoperability
- Unlock seamless data ingestion. Connect any data source into one unified platform, whether structured, unstructured, batch or streaming.
- Power your AI initiatives with near real-time, bi-directional data flows.
- Adapt to any data architecture, ensuring enterprise-grade reliability and governance, with Snowflake’s open and extensible solutions.
Pipeline Lifecycle
Open Lakehouse
AI & Unstructured Data
Ingestion
Developer Experience
Enable reliable data movement
Build, deploy and optimize data pipelines faster
- Streamline the entire pipeline lifecycle and quickly adopt new data engineering practices — or merge with existing workflows.
- Democratize data engineering with Snowflake’s end-to-end workflows, which include a growing set of native capabilities and tight integrations with open standards and data engineering-specific tools.

Centralize data storage in open format
Build or seamlessly integrate your open lakehouse
- Take advantage of flexible open source standards to build your open lakehouse faster, while still getting the reliability and security of the AI Data Cloud.
- Seamlessly integrate with existing lakehouse architectures or build with an open lakehouse format from the ground up, breaking down data silos and getting to value faster

Innovate with AI
Unlock the potential of even the most advanced AI use cases
- Access and process an array of unstructured and semi-structured data with an open, flexible architecture.
- By simplifying the complexities of data engineering across the entire pipeline, Snowflake makes it surprisingly easy to build generative AI applications, enable AI agents with near real-time data flows and more.

Connect from any source
Handle data ingestion built for AI and interoperability
- Unlock seamless data ingestion. Connect any data source into one unified platform, whether structured, unstructured, batch or streaming.
- Power your AI initiatives with near real-time, bi-directional data flows.
- Adapt to any data architecture, ensuring enterprise-grade reliability and governance, with Snowflake’s open and extensible solutions.
Developer Experience
Manage delivery of your AI data foundation
- Focus more efficiently on your work with developer productivity tools like native development environments, Git integration and observability views and alerts.
- DevOps in Snowflake allows you to streamline and automate the software development lifecycle for all your Snowflake environments.

