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| Description | ||||
| Summary | Data and AI observability platform now positioning as an agent trust platform for production AI systems. | |||
| Description | Monte Carlo monitors data pipelines, models, prompts, context, outputs, and production agents to help teams detect, troubleshoot, and remediate data and AI reliability issues. | |||
| Positioning | Agent trust platform for data and AI observability | |||
| Key facts | ||||
| HQ location | San Francisco, CA, USA | |||
| Founded | 2019 | |||
| Employee range | 201-500 | |||
| Funding stage | Series C Plus | |||
| Company type | Private | |||
| Pricing model | custom quote, subscription | |||
| Last updated | Jun 21, 2026 | |||
| Financials | ||||
| Revenue estimate | Unknown | |||
| Valuation estimate | $1.6B valuation at May 2022 Series D; current third-party estimates vary | |||
| Investments | $236M total funding after $135M Series D in May 2022 | |||
| Relationships | ||||
| Target customers | Data engineering, analytics engineering, AI/ML, platform, governance, and reliability teams | |||
| Key competitors | Coralogix, Datadog, Bigeye, Acceldata, WhyLabs, Arize AI, Soda, Fiddler AI | |||
| Known customers | NASDAQ, Honeywell, Roche and hundreds of enterprise data teams publicly referenced | |||
| Segments & Industries | ||||
| Segments | AI Workflows, AI Developer Tools, Knowledge & RAG, AI Quality & Observability, Traditional ML, AI Governance & Risk, Analytics & BI | |||
