Anomalo

Anomalo is an AI-powered data quality company founded in 2018 that has raised $33M to build autonomous data monitoring that eliminates the need for engineers to manually define quality checks. The platform connects to data warehouses and automatically learns the expected distribution, completeness, and statistical properties of every table from historical data, then alerts teams when new data deviates from learned norms. Anomalo's AI-driven approach reduces the time required to achieve comprehensive data monitoring coverage from months of manual rule definition to automated setup in hours. The platform integrates with the modern data stack including dbt, Looker, Tableau, and Airflow and provides root cause analysis tools that help engineers investigate data issues quickly. Anomalo serves data engineering teams at companies where data quality failures have direct business impact, such as financial analytics, customer-facing reports, and ML model inputs. The company has deployed at notable technology companies and differentiates from rule-based monitoring tools through its ability to detect subtle data issues that predefined thresholds would miss. Anomalo positions itself at the intersection of data observability and AI automation, applying ML to the data quality problem itself.