Anomalo formally launched with its product that helps teams trust the data they use to make decisions and build products. Anomalo also raised $33 million in Series A funding, bringing the total raised to $38.95 million. The round was led by Norwest Venture Partners with Two Sigma Ventures, Foundation Capital, First Round Capital and Village Global participating.
The company plans to use the money to rapidly grow its engineering and sales teams to keep up with customer demand.
Anomalo said its customers include some of the biggest brands like BuzzFeed, Discover Financial Services and Substack. The company has exceeded 7-figures of annualized recurring revenue, tripling its revenue over the last quarter.
Legacy approaches to monitoring data quality require extensive work writing data validation rules or setting limits and thresholds. In contrast, Anomalo leverages machine learning (ML) to rapidly assess a wide range of data sets with minimal human input. If desired, enterprises can fine-tune Anomalo’s monitoring through the low-code configuration of metrics and validation rules.
The result, as the company puts it, is a complete data quality platform that is particularly suited to the work of large data teams or enterprises with broad and complex data sets such as those in the financial services, e-commerce and media verticals.