Data Built to Perform

Explore how Under Armour moves as fast as the athletes it serves with unified data, conversational AI and agentic workflows built on Snowflake. “It also has allowed us not to build our own conversational interface from scratch, which would have required a lot of time and maintenance.” On the technical side, [Snowflake CoCo](https://www.snowflake.com/en/product/snowflake-coco/) provides developers with their own coding agent, helping them build faster and serve the business sooner. But one of the most critical shifts has been to put Under Armour’s data within reach of anyone who needed it, not just the people who knew how to wrangle it.

Agent or tool: Snowflake Cortex
Topic: Customer Support
Reported on: Case study (Snowflake)
Added: 2026-11-11

Why it matters

Support is repetitive and time-sensitive. Agents can draft answers, look things up and handle simple requests, so people can focus on the tricky ones. It is one of 554 sightings filed under Customer Support on Agent Sightings (number 464 by interest), and one of 7 involving Snowflake Cortex.

How you could try it

Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into Snowflake Cortex or any similar agent and adjust the details to your situation.

I want an agent to handle routine customer questions end to end, and pass anything unclear to a person. The tool in the source case was Snowflake Cortex.

Saved

Tip: Start small: run it once on a low-stakes example, read what the agent did, and only then let it run on real work.

Source

Read the original first-hand account on Case study (Snowflake): https://snowflake.com/en/customers/all-customers/case-study/under-armour. Our summary is a paraphrase; details are in the source.

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