Wild Alaskan Company Cuts Snowflake Costs by 48% with Yuki, as Yuki Launches Model‑Level Warehouse Optimization for dbt at Coalesce 2025

Wild Alaskan Company, a leading direct-to-consumer platform for sustainably sourced seafood, reduced its Snowflake costs by 48% using Yuki’s real-time optimization platform. Building on this success, Yuki will unveil a new dbt-native feature at dbt Coalesce Summit in Las Vegas, where it is a proud sponsor.

LAS VEGAS, Oct. 12, 2025 (GLOBE NEWSWIRE) -- As Wild Alaskan scaled its data platform, Snowflake costs grew unpredictable and required constant manual intervention. With Yuki, the company cut compute waste, stabilized query performance, and gained predictable budgets in under a month.

“Yuki gave us instant cost visibility and optimization, without pulling engineers off product work,” said Crystal Lee, VP of Data Science & Analytics at Wild Alaskan Company. “We’re running a leaner, faster data platform that scales with growth.”

New dbt-Native Model‑Level Warehouse Optimization at Coalesce 2025

At Coalesce, Yuki will debut its dbt-native integration, designed to give analytics engineers direct visibility into cost and performance at the model level. This means:

• See costs per model — view runtime, cost, and execution timeline for each dbt model.
• Tune warehouse sizes per model — scale up or down the compute per model or job run type.
• Track impact over time — see who changed what, when, and what the cost/runtime deltas were.
• Adopt an investigate, optimize, verify loop — surface anomalies, adjust models, validate outcomes.
  

“dbt has become the backbone of modern analytics engineering,” said Amir Peres, Yuki’s CTO. “With our new dbt-native Model‑Level Warehouse optimization, teams can finally connect performance and cost — making FinOps part of the analytics workflow, not an afterthought.”

Availability & Access

This feature is now live for all Yuki customers. Users can access the “dbt” tab in Yuki’s interface to review execution summaries, model timelines, change histories, and initiate warehouse sizing adjustments per model. For more details, visit: https://yukidata.com/blog/dbt-model-level-optimization/

Case Study Spotlight at Coalesce

Yuki will showcase the Wild Alaskan Company case study during Coalesce 2025, sharing how customers cut +40% of Snowflake compute on average with zero engineering effort. Attendees can see a live demo of both the dbt integration and Yuki’s dynamic warehouse optimization platform and get access to Yuki’s latest dbt repo.

About Yuki

Yuki is the real-time optimization platform for Snowflake. Enterprises use Yuki to cut their data costs by automatically right-sizing warehouses, consolidating queries, and forecasting spend. With one-hour onboarding and enterprise-grade governance, Yuki delivers predictable costs without disrupting performance or engineering teams. 
For more info visit https://yukidata.com/

Contact
Perry Tapiero
Public Relations
perry@yukidata.com 

A photo accompanying this announcement is available at:
https://www.globenewswire.com/NewsRoom/AttachmentNg/d7f2135e-8b4f-4a56-bdc1-93e30801392e

Snowflake Cost Optimization

The Result: 48% Lower Snowflake Costs, In 30 Minutes

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