companies
Monte Carlo Data
Data and AI observability platform that detects broken pipelines, bad data, and unreliable agent behavior before they hit dashboards.
Monte Carlo was founded in 2019 by Barr Moses and Lior Gavish after Moses, then at Gainsight, kept running into the same complaint from data teams: nobody found out data was wrong until a downstream report looked off and someone had to trace the problem backward by hand. The company built what it called data observability - using metadata, query logs, and lineage to automatically flag freshness, volume, and schema anomalies across warehouses and pipelines - and it's since become closely associated with popularizing that category alongside competitors like Bigeye and Metaplane. The platform now connects to Snowflake, BigQuery, Databricks, dbt, and Airflow, among others, and in September 2025 the company extended the same monitoring philosophy to AI agents with Agent Observability, tracking context, performance, behavior, and output quality for production LLM systems. Monte Carlo raised a $135 million round in late 2025 at a reported $1.6 billion valuation, backed by Accel, ICONIQ Growth, and Redpoint, among others, and counts Nasdaq and Roche among its customers.
- Founded
- 2019
- Headquarters
- San Francisco, United States
- Sector
- data
Tools
- Monte Carlo Agent Observability
Monte Carlo monitors AI agents across context, performance, behavior, and output, with tracing, evaluations, alerts, and data lineage.
- Monte Carlo Data Observability Platform
Monte Carlo monitors data, ML models, and AI agents to detect quality issues, trace causes, and improve reliability.