Espresso AI emerges from stealth with $11 million to tackle cloud cost crisis

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Espresso AI, a stealth AI startup from Silicon Valley, has raised more than $11 million in seed funding to bring the power of AI to the biggest challenge in business computing today: reducing the costs of cloud The funding includes a seed round led by Daniel Gross and Nat Friedman, and a pre-round led by Matt Turck at FirstMark, with participation from industry leaders.

The company, which today emerged from stealth, has developed technology that uses advanced language models and machine learning to automatically optimize code and reduce cloud computing costs by up to 80%. Their initial product focuses on streamlining SQL queries for Snowflake, the popular cloud data storage platform.

The opportunity is huge, Espresso AI founder and CEO Ben Lerner said in an exclusive interview with VentureBeat. Snowflake alone has $2 billion in annual revenue. If you look at data warehousing in the big picture, we certainly have hundreds of millions of dollars in revenue for us and billions in potential savings for customers.

A brewing crisis in cloud costs

The move to the cloud has been a double-edged sword for businesses. While cloud platforms offer unparalleled flexibility and scalability, they have also introduced new challenges around cost control and visibility. Many organizations now find themselves struggling with unexpectedly high bills and struggling to forecast and manage their spending.

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Data storage is a particular problem. As companies consolidate data silos and launch new analytics and machine learning initiatives, data warehouses have become some of the biggest consumers of cloud resources. But optimizing these workloads for cost and performance is notoriously difficult.

What we always hear from users is that Snowflake is their second largest line after AWS, Lerner told VentureBeat. And if you go to any Snowflake event, they really focus on two things: cost and performance.

AI to the rescue

Espresso AI’s solution is to harness the power of large language models (LLMs), the core technology behind viral sensations like ChatGPT, to tackle the problem of code optimization. By training these models to deeply understand SQL queries and database architectures, Espresso AI has created a platform that can automatically refactor queries to make them more efficient.

Here’s how it works: Espresso AI connects to a company’s existing Snowflake configuration and continuously analyzes queries running against the data warehouse. Using a combination of natural language processing, program synthesis, and reinforcement learning, it identifies optimization opportunities and rewrites queries on the fly to improve performance and minimize compute usage.

The reason it’s so powerful is that for many existing apps, you need to have a human in the loop to check accuracy, Lerner explained. When you optimize your code, you know what you want it to do, you just go faster. And so we can automatically verify that the optimized code is correct.

Setup is designed to be simple, with the ability to be up and running in less than 10 minutes by changing a single connection string. It’s as easy as changing a URL, Lerner said. Point your BI and analytics tools at the Espresso endpoint instead of directly at Snowflake, and we take care of the rest.

Ready for growth

Espresso AI has already seen strong early traction, with several enterprise customers using its platform to optimize Snowflake production workloads. The company plans to use its funding to accelerate product development and go-to-market efforts.

While Snowflake is the initial focus, the Espresso AI technology is extensible to any SQL data store. Support for platforms like Databricks is on the near-term roadmap. Longer term, the company plans to use its AI optimization engine to accelerate computation across the stack, from data preprocessing to model training.

It’s hard to put a dollar amount on what the world will be like if computers run 100 times faster, Mr. Lerner. Everything will go fast. Well, being able to do more research, more machine learning. There are tons of limitations around computing today.

Of course, providing speedups is 100 times easier said than done. While Espresso AI has shown impressive results in early customer deployments, achieving order-of-magnitude performance gains will require significant research advances. The company will also have to fend off competition from cloud providers themselves, who are investing heavily in cost management and optimization capabilities.

But if Espresso AI can deliver even a fraction of its founding vision, the implications could be profound. With businesses spending more than $600 billion annually on cloud and on-premises computing, the market opportunity for AI-driven efficiency gains is huge.

In an age of belt-tightening and digital transformation, technologies that can deliver significant cost savings without sacrificing performance will find an enthusiastic audience among CIOs. By bringing the power of AI to the unsexy but essential domain of code optimization, Espresso AI may be brewing something truly disruptive.

If a cup of coffee is the price to pay for reducing cloud costs, expect many more IT leaders to line up for a sip of Espresso AI.

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