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November 7, 2025

Launching the Genesis App through the Snowflake Marketplace

Deploy Genesis Directly in Snowflake

Genesis is available as a native Snowflake application. You can deploy it directly in your existing Snowflake environment without adding new infrastructure or external services. The platform runs under your security model and uses your compute, which simplifies adoption and ensures governance requirements are met.

Once the application is active, Genesis agents can begin analyzing your data and creating structured data layers. The platform identifies source tables and organizes them into bronze, silver, and gold layers based on your standards:

  • Bronze contains raw ingested data
  • Silver contains structured and cleaned data
  • Gold contains business-ready data for reporting and analytics

This process is executed through a mission. The mission ensures the workflow is consistent and documented, and that the resulting tables follow the expected structure and logic.

Genesis can then generate a semantic model from the gold layer. This provides a shared view of business metrics and entities. It also makes it easier to work with Snowflake Cortex and other analytics tools without requiring additional modeling frameworks.

Why This Matters

  • Faster time to value on data projects
  • No new control plane or vendor-managed environment
  • A repeatable and governed way to build data models
  • Better alignment between data engineering and analytics teams

With Genesis running inside Snowflake, you get acceleration without platform disruption. Your team continues working in the environment they already understand and trust.

Summary

Genesis can be deployed as a native Snowflake application, running entirely inside the customer’s Snowflake environment under their own security and compute. Once deployed, Genesis agents can analyze data and organize it into bronze (raw), silver (cleaned), and gold (business-ready) layers using a mission to ensure consistency and documentation. From the gold layer, Genesis can generate a semantic model to standardize business metrics and support analytics tooling, including Snowflake Cortex. This approach speeds up data project delivery, avoids adding new infrastructure, provides a governed and repeatable modeling process, and keeps teams working within the platform they already use.

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