# Whatnot at Snowflake Summit 2026

DevFeed: [Whatnot at Snowflake Summit 2026](<https://devfeed.tech/articles/whatnot-at-snowflake-summit-2026-23716.md>)

Original publisher: [Read original article](<https://medium.com/whatnot-engineering/whatnot-at-snowflake-summit-2026-a18a855f529d?source=rss----162aeca881b0---4>)

Author: Whatnot Engineering

Published: 2026-08-12T17:54:54Z

Content type: article

Language: en

Sources: [Whatnot Engineering](<https://devfeed.tech/sources/whatnot-engineering.md>)

Topics: [data](<https://devfeed.tech/topics/data.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [developer velocity](<https://devfeed.tech/topics/developer-velocity.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [data](<https://devfeed.tech/tags/data.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [developer-velocity](<https://devfeed.tech/tags/developer-velocity.md>), [developers](<https://devfeed.tech/tags/developers.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>)

## AI overview

Whatnot's Data Platform team describes the data platform behind its live marketplace and its use of Snowflake Cortex AI and Semantic Views. The approach grounds AI in governed business definitions and trusted metadata so developers can find datasets and metrics and investigate issues using natural-language questions.

## Source excerpt

Earlier this summer, several members of the Whatnot Data Platform team joined Snowflake on stage at Snowflake Summit to share how we're building the data platform behind Whatnot's live marketplace. This post covers what we talked about, why we built it, and future direction. Caption: The Whatnot team were everywhere at the Summit! Snowflake recently published a recap of our sessions, which you can read here: Observability at Scale: Whatnot at Snowflake Summit. Data at Whatnot Every live auction, bid, chat message, purchase, moderation action and recommendation produces data. That translates into billions of events each day powering recommendations, seller analytics, and customer support. For us, data isn't just for internal analysis. We use it to power the product while millions of people are buying and selling in real time. That creates an unique set of engineering challenges. As Whatnot has grown, we've had to evolve our platform to support thousands of datasets, hundreds of developers, and an increasingly diverse set of workloads while maintaining reliability, governance, and developer velocity. At Summit, we talked about the investments we have made to get engineers to vetted data faster Accelerating Builders with AI The Whatnot data platform is a living system. Schemas evolve, pipelines are deployed continuously, business definitions change, and new data products are published every day. Keeping up with that pace of change has become one of the biggest challenges for developers. In our first session, we shared how we're using Snowflake Cortex AI and Semantic Views to make that knowledge more accessible. By grounding AI in governed business definitions and trusted metadata (see this earlier post for more details), builders can ask natural language questions about their data, quickly identify the right datasets and metrics, and investigate issues without manually searching documentation or relying on the Data team. Whatnot's full-time employees now use AI weekly,