Monte Carlo was founded in 2019 by Barr Moses and Lior Gavish in San Francisco. Moses, previously VP at Gainsight, and Gavish, formerly VP Engineering at Sears, had both seen how broken data silently caused bad business decisions. They coined the term “data observability” to describe a category they essentially created.
The platform monitors data pipelines end-to-end and automatically detects anomalies — missing data, schema changes, distribution shifts, freshness issues, and volume anomalies. It works by connecting to the data warehouse, lake, or ETL tools and analyzing metadata without moving the actual data.
Monte Carlo’s approach borrows from application observability (think Datadog for software) and applies it to data. Machine learning models establish baselines for how data normally behaves, then flag deviations. When incidents occur, the platform provides lineage information to help engineers trace problems back to their source.
The company integrates with major data platforms including Snowflake, Databricks, BigQuery, Redshift, dbt, Fivetran, Airbnb, and Looker. This broad coverage means Monte Carlo can monitor data quality across an organization’s entire stack, not just individual components.
Monte Carlo raised $135 million in Series D funding in 2022, reaching a $1.6 billion valuation. Investors include Accel, ICONIQ Growth, and Redpoint Ventures. The company serves hundreds of enterprise customers, including Fox, JetBlue, and PagerDuty.
Moses serves as CEO and has become a prominent voice on data reliability topics. The company employs approximately 250 people.
