Espresso AI, an innovative platform leveraging large language models (LLMs) to optimize data warehouses, has announced the launch of a groundbreaking solution designed to transform Databricks into an agentic lakehouse. Developed by a team of former Google engineers, the platform applies advanced AI research to significantly enhance utilization and slash costs by up to 50%.
Espresso AI launched out of stealth last year and made its mark by initially targeting Snowflake, one of the leading data warehouse platforms. The company has now expanded its support to include Databricks, which is one of the fastest-growing data lakehouse ecosystems. This strategic move reflects the company’s goal to deliver AI-driven optimization solutions across major cloud data platforms that help organizations maximize their investments with minimal manual effort.
Powering Data Warehouses with Intelligent Optimization
As Databricks experiences rapid growth—with an estimated annual revenue surpassing $4 billion and a valuation exceeding $100 billion after its August 2025 funding round—the platform seeks to address common inefficiencies in data management. But despite its popularity, many users struggle with underutilized resources, leading to inflated operational costs.
Ben Lerner, CEO of Espresso AI, emphasized the significance of this expansion: “Databricks is seeing explosive growth with their Data Lakehouse product. To compete with Snowflake’s adoption, they need to ensure their users are as optimized and cost-efficient as possible. Our platform enables Databricks customers to cut their bills in half while boosting performance, all without manual effort.”
A Proven Track Record and Strong Backing
Founded by ex-Googlers—Ben Lerner, Alex Kouzemtchenko, and Juri Ganitkevitch—who previously worked on machine learning, systems performance, and deep learning in Google Search, Google Cloud, and DeepMind, the company secured $11 million in seed funding from notable investors including FirstMark Capital, Nat Friedman, and Daniel Gross.
Following a successful six-month beta involving major enterprises such as Booz Allen Hamilton and Comcast, early feedback has been remarkably positive. Nataliia Mykytento, Head of Engineering at Minerva, shared her experience: “Espresso AI cut our costs in half with no effort on our part. They’ve been instrumental in managing our rapidly growing expenses.”
Getting set up with Espresso AI is a very quick process. In under 10 minutes, companies can take advantage of Espresso AI by changing a single connection string; users point their Business Intelligence (BI) and analytics tools to the Espresso endpoint, instead of directly to Snowflake or Databricks, and immediately start saving money. To date, Espresso AI has raised $11Million in seed funding led by Daniel Gross and Nat Friedman.
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