SnapLogic, a leader in generative integration, is offering new connectivity and support for Snowflake vector data types, Snowflake Cortex, and Streamlit, assisting companies modernize their businesses and accelerate the creation of generative AI applications.
According to the companies, now customers can leverage SnapLogic’s ability to integrate business critical information into Snowflake’s high-performance cloud-based data warehouse to build and deploy large language model (LLM) applications at scale in hours instead of days.
GenAI Builder now supports Snowflake vector data types, in addition to Pinecone vector database, giving customers the option to select between the two industry-leading vector stores, allowing them to harness the scale and speed of their Snowflake data warehouse.
Earlier this year, SnapLogic introduced GenAI Builder, the world’s first no-code generative AI application development product for enterprise applications and services. By leveraging vector data types, GenAI Builder allows organizations to quickly build highly tailored and accurate LLM-powered enterprise applications that accelerate and introduce new business processes.
GenAI Builder supports a wide variety of use cases including creating co-pilot assistants that allow employees to get answers about HR related questions, help legal teams automatically redline contracts, or help finance analyze market data.
Similarly, SnapLogic now supports Snowflake Cortex, a fully managed service that offers machine learning and AI solutions to Snowflake users while adhering to the Snowflake security parameter. This allows SnapLogic users to leverage Snowflake’s security, scalability, and governance capabilities while building their LLM applications. Snowflake Cortex solutions can benefit from Snowflake’s existing security, scalability, and governance capabilities, according to the companies.
Additionally, SnapLogic introduced support for Streamlit, a powerful framework for creating interactive web applications with Python. This allows data engineers to create powerful LLM and data analysis applications directly from their existing Python code, eliminating the need to rely on application engineers and IT to build applications from the ground up.
The advantage of leveraging Snowflake to develop new LLM-powered applications is that it eliminates the time-consuming workflows previously required to create user interfaces for these applications. This enables companies to build and deploy GenAI applications more rapidly, according to Snowflake and SnapLogic.
"We are thrilled to announce SnapLogic's enhanced integration capabilities with Snowflake vector data types, Cortex, and Streamlit, to help organizations create new generative AI-powered applications at scale,” said Jeremiah Stone, CTO of SnapLogic. "Not only are organizations struggling to create accurate enterprise GenAI-powered applications due to their inability to connect critical data sources, they are also facing new challenges in creating those applications more quickly and with limited coding talent. By combining the enterprise application breadth of SnapLogic and the ingenuity of GenAI Builder with the efficiency and power of Snowflake, we are helping eliminate those barriers.”
SnapLogic's integration support for Snowflake Vector Data Type, Snowflake Cortex, and Streamlit are now available to all SnapLogic customers.
For more information about this news, visit www.snaplogic.com or www.snowflake.com.