Espresso AI Raises $11M to Cut Cloud Costs with Generative AI

Espresso AI Raises $11M to Cut Cloud Costs with Generative AI

Silicon Valley-based startup, Espresso AI, has emerged from stealth with ambitions to leverage generative AI to reduce soaring cloud compute costs. The company announced it has raised over $11 million in funding, including a seed round led by Daniel Gross and Nat Friedman, and a pre-seed round led by Matt Turck at FirstMark, with participation from industry luminaries like Tasso Argyros, Spencer Kimball, and Calvin French-Owen.

Founded by Ben Lerner, Espresso AI has developed an AI-powered platform that automatically optimizes code to reduce cloud compute costs. Its first product focuses on streamlining SQL queries for Snowflake, the popular cloud data warehousing platform, and has already reduced customers' bills by as much as 80%.

The move to the cloud has been a double-edged sword for enterprises. While it offers flexibility and scalability, it has also introduced challenges around cost control and visibility. Data warehousing, in particular, has become a major pain point as companies consolidate data silos and launch new analytics initiatives.

Espresso AI's solution uses large language models to deeply understand SQL queries and database architectures. By analyzing queries run against a data warehouse, it identifies optimization opportunities and rewrites queries on the fly to improve performance and minimize compute usage. Setup is designed to be simple, with the ability to get up and running in under 10 minutes.

While Snowflake is the initial focus, Espresso AI's technology is extensible to any SQL data warehouse, with support for platforms like Databricks on the near-term roadmap. Longer-term, the company envisions using its AI optimization engine to speed up compute across the stack.

"It's hard to put a dollar amount on what the world will look like if computers run 100 times faster," said Lerner. "Everything's going to go fast. We'll be able to do more research, more machine learning. There are tons of constraints around compute today."

With enterprises spending over $600 billion annually on cloud and on-prem compute, the market opportunity for AI-powered efficiency gains is massive. As companies tighten their belts and pursue digital transformation, solutions like this that could drive meaningful cost savings without sacrificing performance are likely to find an eager audience among IT leaders.

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