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