• Chaos Genius’ patent-pending technology analyzes Snowflake workloads with millions of queries by using query patterns.
• Chaos Genius says it can help an organization cut costs by up to 30% by giving them instant visibility into their Snowflake footprint and optimizing workloads to improve query performance.

Chaos Genius, a DataOps observability startup, plans to expand after closing on a USD 3.3 million seed funding round, led by Elevation Capital.

Angel investors like former Cloudera Inc. General Manager Charles Zedlewski, Kabam Inc. co-founder Holly Liu, and Sumon Sadhu were part of the round, along with Y Combinator.

Chaos Genius, officially called GoodHealth Technologies Inc., has developed a distinct data infrastructure observability and an optimization product first aimed at Snowflake Inc.’s cloud data warehouse platform.

As the company says, many enterprise data teams have become dependent on third-party data warehouses like Snowflake to organize their data.

Data warehouses make it simple for teams to consolidate their data in a single location, making it easier to examine. But cloud data warehouse services can cost thousands of dollars a month, so it’s essential to figure out how to use them most efficiently.

This is what Chaos Genius does. Its Snowflake observability and cost optimization tools take the load from data teams.

The company’s patent-pending technology analyzes Snowflake workloads with millions of queries using query patterns. The platform works by figuring out which queries in a workload are the least efficient. Then it gives smart suggestions to make them more efficient and save money.

Chaos Genius says it can help an organization cut costs by up to 30% by giving them instant visibility into their Snowflake footprint and optimizing workloads to improve query performance. Chaos Genius explicitly stated that this number was not chosen randomly.

It cites a McKinsey paper from earlier last year that details how firms may reduce their data spending by 15% to 35% by optimizing their data sources, infrastructure, governance, and consumption.

Chaos Genius also helps data engineers avoid the time-consuming task of analyzing database workloads to identify expense peaks. According to the startup, these jobs have typically always been carried out manually.

The business claimed that several Snowflake clients who spend over one million dollars annually are testing out their platform, which is presently accessible in beta.

Preeti Shrimal, co-founder and CEO of Chaos Genius claimed that her company’s products are even more useful now as businesses are under pressure to make cuts due to the economic slump. “With a unique set of features, like analyzing query patterns, finding unused data, and intelligent recommendations, our product makes a massive impact on how data teams use their warehouses and saves up to 30% in data costs for our customers,” she added.

Later this year, the Chaos Genius platform will go generally available thanks to the financing from the recent round. The business also plans to broaden the scope of its tools to include other well-known data lakes and warehouses, like Databricks, Google BigQuery, and Amazon Redshift.