Today, we are thrilled to announce that Box is a launch partner for Snowflake Openflow. Generally available today, this integration allows developers and data engineers to seamlessly connect unstructured content in Box with the powerful analytics capabilities of Snowflake, unlocking new insights and automating data-driven workflows.
Enterprises today are sitting on a goldmine of data, much of it locked away in separate silos. Structured data resides in platforms like Snowflake, ready for analysis, while a vast amount of valuable unstructured data – documents, images, presentations – lives within Box. Bridging this gap to unlock true business intelligence and power the next wave of AI has traditionally been a challenge. It often involved significant manual labor, such as sifting through files for key information, and required significant collaboration across teams to map unstructured content insights with structured datasets. Our new connector is designed to simplify these workflows and streamline the integration process.
Introducing the Snowflake Openflow connector for Box
Snowflake Openflow simplifies data integration, creating a powerful bridge between the Box Intelligent Content Management platform and the Snowflake AI Data Cloud. A key feature of this new connector is its ability to ingest Box user permissions alongside with content. This allows downstream Snowflake applications to query data while honoring the original access controls set in Box, ensuring secure and compliant access to insights.
The Snowflake Openflow connector for Box enables you to:
- Leverage Snowflake metadata templates: Define a template in Box that mirrors Snowflake metadata tables.
- Extract metadata from Box content: Pull key information, text, and attributes from documents, images, and more stored in Box.
- Combine with Snowflake data: Enrich your existing structured datasets in Snowflake with this newly extracted metadata.
- Enhance Box content: Send enriched or newly generated metadata back to Box, updating and adding value to your original content.
This bidirectional flow allows you to create powerful, automated workflows that previously required significant manual effort, such as looking through files to find key-value pairs and mapping them to data in Snowflake.
Why this matters for developers and data engineers
For developers and data engineers, this connector opens up new possibilities. Many may not be aware of Box's robust metadata extraction capabilities, powered by Box AI. This integration provides a direct, streamlined way to:
- Leverage unstructured data in Box: Treat your Box content as a critical component of your AI and analytics applications without needing to move the files themselves.
- Gain deeper insights: Correlate information from contracts, reports, and images in Box with sales figures, customer data, and operational metrics in Snowflake.
- Automate workflows: Build applications that automatically extract information from incoming documents in Box and feed it into Snowflake for analysis or trigger downstream processes.
As Ben Kus, Chief Technology Officer at Box, stated, “The strategic partnership between Box and Snowflake combines the leading platforms for both their unstructured and structured data to use the power of AI to unlock the value of their data like never before. Together, we’re removing the complexity of data integrations so customers can maximize value and accelerate outcomes across the entire content lifecycle.”
Deep dive into metadata extraction use cases
To illustrate the power of this new connector, we’ve demoed two use cases for metadata extraction.
- Metadata extraction to Snowflake: Box AI can be used to extract metadata from contract files stored in Box, based on a pre-configured Box metadata template. This extracted metadata was then ingested directly into a Snowflake database table. Once in Snowflake, this data can be used in other processes or combined with information from existing tables in your data warehouse.
- Metadata enrichment and write back to Box: Metadata residing in the Snowflake table and applied custom business logic to enrich it. The enhanced metadata was written back to Box, populating a new metadata template applied to the contracts.
This demo highlights the power of combining Box and Snowflake. While we focused on contracts, enterprises can extend this by combining multiple systems or connectors to create fully automated, agentic workflows applicable to any industry.
Start building today
The new Snowflake Openflow connector for Box is a significant step towards a more unified, AI-ready data landscape. It empowers developers and data engineers to harness the full potential of their enterprise data, both structured and unstructured.
Learn more about Snowflake Openflow and check out these instructions to start using the Box connector today to transform your data workflows.
