Espresso AI reduces data warehouse bills by changing how queries execute on Snowflake and Databricks. Warehouse spend is one of the least examined lines in most engineering budgets, because the invoice arrives as a single figure with no attribution to the queries that caused it.
Attacking it at the query level is the right layer. Most teams respond to a large bill by resizing the warehouse, which changes the number without addressing the work that produced it.
A savings estimate is offered before committing, which is a reasonable way to evaluate this kind of product. The percentages quoted on the site are the vendor’s own figures, it needs access to the warehouse to do anything, and none of it is worth the effort below meaningful spend.
