Written by 6:48 am AI:ML, Cloud, Featured

Snowflake introduces LLM-driven Document AI for unstructured data use cases 

Snowflake Data Summit 2023 had a number of key announcments

Snowflake data summit

The Snowflake Summit 2023, the company’s annual user conference, witnessed a number of LLM-based announcements and a host of enhancements to the company’s Data Cloud platform. The most notable one, perhaps, is its Document AI which stems from Snowflake’s acquisition of Applica (Sept. 2022) and leverages its purpose-built, multimodal LLM.  Document AI, which is currently in private preview, will enable businesses to extract and leverage unstructured data from documents. 

Over the next five years, over 90 percent of the world’s data will be unstructured in the form of documents, images, video, audio, and more according to IDC2. This massive volume of unstructured data is routinely stored by organizations, however gaining valuable insight from it has historically required manual, error-prone processes and limited expert skillsets. Snowflake’s built-in Document AI will make it easier for organizations to understand and derive value from unstructured data and documents using natural language processing, said Murad Wagh, Director of Sales Engineering at Snowflake, while addressing the Indian media.

Some of the use case examples include the ability to easily extract content like invoice amounts or contractual terms from documents and fine-tune results using a visual interface and natural language. Snowflake is starting with Document AI and plans to expand these capabilities to more types of unstructured data.

Additionally, the company also announced updates for Iceberg Tables, which will enable organizations to work with data in their own storage in the Apache Iceberg format, whether that data is managed by Snowflake or managed externally. Snowflake also announced that its platform will support a broader set of advanced analytics capabilities including pre-built machine learning functions for SQL users (public preview), and is expanding its unified governance and privacy with new data quality metrics and classification features (both in private preview). 

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