Monte Carlo is a Data Observability company founded in 2019 and based in San Francisco, United States. It has raised $220M in total funding, most recently a Series D in 2022 at a $1.6B valuation.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| May 24, 2022 | Series D | $135M | $1.6B | IVP |
| Aug 1, 2021 | Series C | $60M | — |
| ICONIQ Growth |
| Feb 1, 2021 | Series B | $25M | — | Accel |
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A data quality and observability platform that connects to warehouses, data lakes, ETL tools, and BI tools to detect data anomalies using ML-based baseline monitoring without manual threshold configuration. Provides automated root cause analysis, blast radius mapping, and data lineage to reduce time-to-resolution for data incidents. Named 2026 Snowflake Data Governance Partner of the Year.
Launched September 2025, extending Monte Carlo's platform to monitor AI agent inputs, outputs, and production behavior. The first product to unify data and AI observability in a single platform, enabling teams to detect poor AI outputs using LLM-as-judge or deterministic evaluations, flag performance degradations, and trace failures back to upstream data quality issues.
Launched May 2025, this capability extends Monte Carlo's observability suite to unstructured data assets including logs, PDF documents, Word files, and PowerPoints. Enables data teams to monitor quality and freshness for the document and artifact layer of AI pipelines, complementing structured data monitoring across the full modern data stack.