Monte Carlo

Monte Carlo Data is a US company founded in 2019 and headquartered in San Francisco, California, offering a data and AI observability platform that helps data teams detect and resolve data quality issues before they reach downstream reports or AI agents.

The platform continuously monitors pipelines and warehouses for freshness, volume, schema and distribution anomalies, then extends monitoring to production AI agents through an agent-observability and MCP-based toolkit. It is used by more than 400 enterprises, including T. Rowe Price, Target, PepsiCo and Cisco, to reduce data downtime across analytics and agentic workloads.

1. Data observability: monitors freshness, volume, schema and distribution anomalies automatically.

2. Agent observability: tracks behavior and data usage of production AI agents.

3. Root cause analysis: traces data incidents back to the originating pipeline or table.

4. Lineage mapping: visualizes upstream and downstream impact across the data stack.

5. Agentic operations: automates onboarding and fleet management for monitored assets.

6. Broad integrations: connects with major cloud warehouses, lakehouses and orchestration tools.