Anomalo's machine learning approach to data quality is growing like gangbusters

Anomalo, a startup that uses machine learning to solve data quality problems, has raised $33 million in a Series B funding round, bringing its total funding to $72 million. The company, founded by former Instacart employees, has seen its relevance grow as data quality becomes increasingly important for large language models. The firm has grown 15x since its Series A round, with its annual recurring revenue growing by 177% in the recent fiscal third quarter. The new funding will be used to double the company's workforce, which currently stands at 50.

The Series B round was led by SignalFire, with participation from strategic investor Databricks Ventures and previous investors Norwest Venture Partners, Two Sigma Ventures, and Foundation Capital. Anomalo's services have become more crucial as companies store more data in cloud storage and data warehouses like Databricks and Snowflake. The company has also made strides in diversity, with four out of seven executives hired since the A round being women, and a third of the engineering group being women.

Key takeaways:

Anomalo, a startup that uses machine learning to solve data quality problems, has raised $33 million in a Series B funding round, bringing its total raised to $72 million.
The company has grown 15x since its Series A funding round, with its annual recurring revenue growing by 177% in the recent fiscal third quarter.
Anomalo plans to use the new funding to double its current workforce of 50 employees. The company is also working towards improving diversity, with a third of its engineering group being women.
The Series B investment was led by SignalFire, with participation from Databricks Ventures, Norwest Venture Partners, Two Sigma Ventures, and Foundation Capital.

Anomalo's machine learning approach to data quality is growing like gangbusters | TechCrunch

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