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Monte Carlo

https://montecarlo.ai/ Research Team Data
Active

Data and AI observability platform now positioning as an agent trust platform for production AI systems.

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 (201-500)
Funding stage
Series C Plus
Company type
Private (Private)
Pricing model
Custom Quote Subscription (Enterprise subscription / quote-based)
Last updated
Jun 21, 2026

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

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

Classification (raw research text)

Core focus
Data, AI and agent observability
Core industry
Data Observability / AI Reliability
Core category
Data + AI observability platform

Shown verbatim from the research spreadsheet — deriving structured segment/industry tags from this text is a future phase.

Attribute breakdown

  • AI Workflows Secondary feature
  • System / API Integration Secondary feature
  • Prompt Management / Prompt Engineering Secondary feature
  • Retrieval-Augmented Generation Secondary feature
  • AI / LLM Data Pipeline Primary focus
  • Traditional Machine Learning Secondary feature
  • AI Quality Assurance / LLM Evaluation Secondary feature
  • AI Observability / Monitoring Primary focus
  • AI Security / Guardrails Secondary feature
  • Data Privacy / PII / Confidential AI Secondary feature
  • AI Governance / Policy Management Secondary feature
  • AI Risk / Compliance Secondary feature
  • AI Asset Inventory / Model Registry Secondary feature
  • Human-in-the-Loop Review / Feedback Secondary feature
  • Analytics / BI / Decision Intelligence Secondary feature
Show all 32 attributes
  • AI Workflows Secondary feature
  • AI Automation / Business Process Automation Not emphasized
  • AI Fine-tuning / Custom Model Training Not emphasized
  • Agent Builder / Agent Configuration Not emphasized
  • Multi-agent Orchestration / Runtime Not emphasized
  • System / API Integration Secondary feature
  • Prompt Management / Prompt Engineering Secondary feature
  • Retrieval-Augmented Generation Secondary feature
  • Graph RAG / Knowledge Graph Retrieval Not emphasized
  • Enterprise Search / Knowledge Management Not emphasized
  • AI / LLM Data Pipeline Primary focus
  • Document AI / Document Processing Not emphasized
  • Model Deployment / Inference Infrastructure Not emphasized
  • Traditional Machine Learning Secondary feature
  • AI Quality Assurance / LLM Evaluation Secondary feature
  • AI Observability / Monitoring Primary focus
  • AI Security / Guardrails Secondary feature
  • Data Privacy / PII / Confidential AI Secondary feature
  • AI Governance / Policy Management Secondary feature
  • AI Risk / Compliance Secondary feature
  • AI Asset Inventory / Model Registry Secondary feature
  • Human-in-the-Loop Review / Feedback Secondary feature
  • Call Transcription / Speech-to-Text Data Capture Not emphasized
  • Conversation Intelligence / Speech Analytics Not emphasized
  • Text Chatbots / Conversational Assistants Not emphasized
  • Voice AI Agents Not emphasized
  • Voice Infrastructure / STT / TTS Not emphasized
  • AI for Customer Experience / Support Automation Not emphasized
  • Sales / Revenue Intelligence Not emphasized
  • Analytics / BI / Decision Intelligence Secondary feature
  • Enterprise App / Internal Tool Builder Not emphasized
  • Vertical-Specific AI Not emphasized