NEW YORK, Aug. 06, 2025 (GLOBE NEWSWIRE) -- Espresso AI, the LLM-Driven Cost Optimization Platform for data warehouses, today launched a Kubernetes Scheduler for Snowflake that intelligently routes queries between warehouses in real time. Espresso AI was founded by ex-Googlers who worked on Google DeepMind and have applied their AI research to optimize utilization and reduce costs by 50% for Snowflake users.

Snowflake does not support dynamic scheduling between warehouses, forcing customers to pick between large, overprovisioned warehouses and fragmented underutilized warehouses, causing performance constraints and budget overruns. The Kubernetes Scheduler for Snowflake from Espresso AI solves this long-standing problem. It’s a proxy between Espresso’s users and Snowflake’s data warehouses. When users or tools send a query to Snowflake, the AI-driven scheduling agent re-routes the query to an appropriate cluster based on computing resources requirements.

“We’re threading the needle by dynamically allocating workloads – our Kubernetes scheduler will route queries based on available capacity so that you don’t unnecessarily spin up new clusters,” said Ben Lerner, CEO and Co-Founder of Espresso AI. “You can think of it as Uber Pool for your queries – if there’s room in a warehouse that’s already running, we make sure you run your workloads there and utilize the compute you’re already paying for.”

The core idea behind the scheduler is separating logical compute from physical compute. Instead of having a fixed warehouse for each workload – leading to fragmentation, underutilization, and higher bills – Espresso AI maps each request to any warehouse with available resources.

In situations where no existing warehouse can handle the request without backing up queries and degrading performance, Espresso AI will automatically spin up a new warehouse – and then automatically spin it back down when it is no longer needed. This leads to massive savings of up to 50% on Snowflake bills.

“Espresso AI has been super easy to integrate and got us immediate, measurable cost savings on our Snowflake spend,” said Tim Hsu, Engineering Manager at Goldbelly. “It is definitely one of the highest ROI cost savings initiatives we’ve had.”

Espresso AI was founded by three ex-Googlers - Ben Lerner, Alex Kouzemtchenko, and Juri Ganitkevitch - who previously worked on machine learning, systems performance, and deep learning research in Google Search, Google Cloud, and Google DeepMind. The company has raised $11 Million in seed funding from FirstMark Capital, Nat Friedman, and Daniel Gross.

About Espresso AI
Espresso AI uses machine learning to optimize Snowflake in real time. Founded by ex-Googlers, their platform applies research from DeepMind to significantly reduce Snowflake costs.

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