Inside Brilliant Earth's AI Transformation with Snowflake + Posit

Before Snowflake, Brilliant Earth's data science teams relied on manual Excel and legacy data warehouse workflows, creating data silos and query bottlenecks that made advanced analysis difficult.

By centralizing their data in Snowflake and pairing it with the Posit Team Native App for data science, they gave their teams an AI-powered, scalable, and governed environment to build predictive models, sharpen customer segmentation, and put trusted insights directly in the hands of decision-makers.

Join Snowflake, Posit, and special guest Matthias Mueller, Brilliant Earth, for a candid look at how the leading omnichannel jeweler modernized its analytics stack. 

In this session, you'll learn how:
 

• Brilliant Earth centralized fragmented data into Snowflake as a single, governed source of truth, freeing data scientists to spend time on analysis instead of moving data between systems.

• Their team built and iterated on predictive models and sharper customer segmentation by pairing Snowflake's scalable data foundation with Posit's data science environment, enabling faster model development in R and Python and more targeted, personalized customer engagement.

• They put trusted insights directly in the hands of decision-makers by deploying dashboards, applications, and reports through Posit for non-technical marketing, merchandising, and executive teams. To quickly and easily share key insights, the team built an AI-powered summarization capability using LLMs that leverages Anthropic and Snowflake Cortex APIs.

• Brilliant Earth embeds Positron (for development), Snowflake Cortex AI, and Posit Connect (for publishing) in their workflow, so their data science team can now govern data rigorously, deploy insights rapidly, and bring AI into the process in a way that keeps human experts firmly in control.