For decades, organizations have sought to lower the barrier to analytics. In an ideal world, all teams, regardless of data skill level, would have access to the data they need to extract actionable insights. While the rise of large language models (LLMs) has brought us closer to realizing this goal, significant challenges remain. Our new integration with Snowflake Cortex represents a significant advancement in overcoming these obstacles, providing a seamless, secure, and efficient pathway to harnessing the full potential of generative AI (GenAI).

Overcoming GenAI Challenges with Snowflake

Organizations are grappling with the complexities of implementing GenAI applications, particularly regarding security, trust, and efficiency. Snowflake addresses many of these challenges with its robust platform, primarily through Snowflake Cortex and Snowpark Container Services. Snowflake Cortex is a cost-effective, managed service that leverages LLM and ML functions for advanced analytics, enabling users to perform tasks like querying and predictive analysis without managing infrastructure, with compute optimized for secure, governed data. Snowpark Container Services allows users to deploy, manage, and scale containerized AI applications directly within the Snowflake ecosystem, keeping data securely in place for processing. By combining these capabilities, Snowflake offers a high-performance, secure, and seamless solution for deploying and managing GenAI applications.

Build Trust in GenAI with the AI Context Engine™ from

Trust is the most critical of all hurdles — until it’s overcome, organizations will remain hesitant to adopt GenAI applications broadly. To bridge the trust gap, offers the AI Context Engine, which connects LLMs with your organizational data and business context. At the heart of is a knowledge graph, which you might liken to the language of AI. This knowledge graph integrates metadata, processes, policies, people, and systems, allowing users to ask complex questions and receive accurate, contextual answers. By embedding business context into AI interactions, the AI Context Engine enables more precise answers to be delivered and relevant insights to be surfaced, making it a powerful tool for businesses looking to harness the full potential of their business data.

Additionally, the AI Context Engine shows precisely where the answers come from, enhancing trust and reducing the risks associated with AI deployment—especially for organizations where transparency and auditability are crucial. It provides a clear traceability path for AI-generated insights, ensuring that users can understand and verify the origins and reasoning behind each response. By leveraging this technology, organizations can achieve a higher level of confidence in their AI-generated insights, making it easier to adopt and scale GenAI solutions.

A Winning Combination: and Snowflake Cortex

The combination of’s AI Context Engine with Snowflake Cortex addresses security and trust concerns within the Snowflake environment. App developers and data engineers can now leverage's capabilities by simply calling a function within Snowflake. This solution enables organizations to accelerate the development of AI experiences while minimizing the total cost of ownership.

Here are a few use cases:

Watch Snowflake’s 5 Minute Demo Dare from May 16. We showcase how we combined these capabilities to demonstrate how businesses can transform their interactions with data.

Overcome GenAI Hurdles with and Snowflake

In a world where data is the key to unlocking business potential, the integration of’s AI Context Engine with Snowflake Cortex marks a significant step forward. By addressing the critical challenges of security and trust and opening the door to simpler, more expedient ways of building AI experiences, this partnership empowers organizations to leverage GenAI's capabilities in days, not months.

Learn more about the integration by contacting our team.