Accelerate AI adoption, build AI-powered data products, and grow your business
Meet our team at Snowflake Data Cloud World Tours!
Toronto | September 22
NYC | October 2
Chicago | October 6
Paris | October 8
London | October 10
Stockholm | October 14
Omni and Snowflake help customers...
Deliver true self-service
Anyone can get insight from Snowflake data using SQL, Excel functions, point-and-click, and AI
Eliminate data engineering bottlenecks
When new data lands in Snowflake, users can analyze metrics immediately, without data engineers modeling it first
Consolidate your data stack
Omni brings together a built-in semantic layer, fast data exploration, beautiful visualizations, and governed BI in a single platform atop Snowflake
Scale access to data (not headcount)
Support data-driven decision-making and powerful data products — with minimal administration
Speed up analytics development
Facilitate fast ad-hoc analysis, rapid iteration, and an easy path to standardization – helping your data team keep pace with the business
Build exceptional user-facing analytics
Omni makes it easy to create customized, interactive data products to meet performance SLAs – especially when supported by Snowflake’s concurrency scaling
Omni’s integrations help you leverage Snowflake’s AI capabilities
Snowflake semantic views
Unlock trustworthy AI everywhere by using Snowflake semantic views alongside Omni’s built-in semantic model. Define datasets and metrics across tools to give teams a fast, flexible foundation for analyzing data.
Snowflake Cortex
Bring AI into everyday use cases with data enrichment, sentiment analysis, categorization, and AI chat powered by Snowflake's LLM functions + Omni.
Omni’s AI answered like a consultant and provided recommendations that aligned with a proposal our team was already pursuing. It validated the AI’s capabilities and helped us build stakeholder confidence — giving our stakeholders confidence and strengthening alignment around SWBC’s AI vision.”- Austin Aranda, Director of Data Solutions
Omni’s built-in semantic model helps data teams quickly build enterprise data applications. Being able to validate metric definitions allows users to improve the accuracy of models to produce trustworthy results, which is essential for enterprise AI use cases.- Josh Klahr, Head of Data Warehousing at Snowflake & Harsha Kapre, Director at Snowflake Ventures