Monte Carlo

Monte Carlo is a technology company.

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Updated: Feb 17, 2026 ·

Recent News & Mentions

May 1, 2022FundingMonte Carlo - Series D Aug 1, 2021FundingMonte Carlo - Series C Feb 1, 2021FundingMonte Carlo - Series B Sep 1, 2020FundingMonte Carlo - Series A

Financial History

Monte Carlo has raised $241.0M across 4 funding rounds. Most recently, it raised $140.0M Series D in May 2022.

Total Raised

$241.0M

Valuation

N/A

Funding Rounds Raised

Date	Round	Other Investors
May 1, 2022	$140.0M Series D	Accel, AirAngels, Andreessen Horowitz, Aya, B Capital Group, Cedar Capital Group, Cornerstone Venture Partners, Craft Ventures, CRV, Cyberstarts VC, Felicis Ventures, Greylock, IVP, Notable Capital, Operator Collective, Predictive VC, Redpoint Ventures, Sequoia Capital, Single Fin Ventures, Theory Ventures, Todd and Rahul's Angel Fund, XYZ Venture Capital, Y Combinator, Allison Pickens (Allison Pickens Ventures), Ameet Patel, Scott Belsky
Aug 1, 2021	$60.0M Series C	Accel, AirAngels, Andreessen Horowitz, Aya, Cornerstone Venture Partners, Craft Ventures, Cyberstarts VC, Felicis Ventures, Notable Capital, Operator Collective, Predictive VC, Sequoia Capital, Theory Ventures, Todd and Rahul's Angel Fund, XYZ Venture Capital, Y Combinator, Allison Pickens (Allison Pickens Ventures), Ameet Patel, Scott Belsky
Feb 1, 2021	$25.0M Series B	Accel, AirAngels, Andreessen Horowitz, Aya, Cornerstone Venture Partners, Craft Ventures, Cyberstarts VC, Felicis Ventures, Notable Capital, Operator Collective, Predictive VC, Sequoia Capital, Theory Ventures, Todd and Rahul's Angel Fund, XYZ Venture Capital, Y Combinator, Allison Pickens (Allison Pickens Ventures), Ameet Patel, Scott Belsky
Sep 1, 2020	$16.0M Series A	Accel, Aya, Craft Ventures, Cyberstarts VC, Notable Capital, Todd and Rahul's Angel Fund, Ameet Patel

Financial History

Monte Carlo has raised $241.0M across 4 funding rounds.

Total Raised

$241.0M

Valuation

N/A

Leadership Team

Key people at Monte Carlo.

Sai Senthilkumar

Board Observer

Leadership Team

Key people at Monte Carlo.

Sai Senthilkumar

Board Observer

Deep Dive

High-Level Overview

Monte Carlo is a San Francisco-based technology company founded in 2019 that builds an end-to-end data and AI observability platform to ensure the reliability and accuracy of data pipelines.[1][2][4] It serves data teams at large enterprises like Block, Buzzfeed, Notion, Fox, PepsiCo, Amazon, and American Airlines by monitoring cloud warehouses, lakes, ETL tools, and BI systems for anomalies, downtime, and quality issues using metadata collection, data lineage reconstruction, and machine learning.[1][2][3][4] The platform solves data downtime—missing, inaccurate, or unreliable data—through plug-and-play integrations, automated incident detection, and resolution, enabling trusted data for AI and business decisions; it operates on a pay-as-you-go SaaS model based on monitored tables, with over 400 enterprise customers, 10M tables monitored, and 1,000 incidents resolved daily as of recent metrics.[1][4] Growth has been strong, with ARR nearing $15M in early 2024 (177% YoY), doubled Fortune 500 customers in Q3 2023, and 2025 recognitions including G2's #1 Data Observability Platform for eight quarters and Databricks Data Governance Partner of the Year.[1][2]

Origin Story

Monte Carlo was founded in 2019 by CEO Barr Moses, who coined the term "data observability" and identified a critical gap in monitoring data pipelines amid the rise of modern data stacks.[1][4] Moses and the team launched the company to address the lack of tools guaranteeing data trust, especially as businesses relied on data for digital products and decisions without easy visibility into pipeline health.[2][4] Early traction came from enterprises needing end-to-end coverage across fragmented tools; by 2023, it secured notable customers like Block and Notion, raised $236M from investors including Accel, ICONIQ Growth, GGV Capital, Redpoint, IVP, and Salesforce Ventures, and doubled Fortune 500 adoption in Q3 2023.[1][2] Pivotal moments include defining the data observability market in 2019 and expanding into AI observability by 2025 to tackle GenAI data challenges, evolving from data reliability to comprehensive AI pipeline trust.[1][4]

Core Differentiators

Monte Carlo stands out in the crowded data quality space through these key strengths:

End-to-end coverage and plug-and-play setup: API-based connectors provide out-of-the-box monitoring for cloud warehouses (e.g., Snowflake, BigQuery), ETL, lakes, and BI tools, reconstructing field-level lineage to track upstream changes' downstream impacts without touching raw data.[1][3][5]
Detection-first philosophy with ML-powered anomaly detection: Scans for structural changes, quality issues, drift, and failures across pipelines and AI systems, resolving 1,000 incidents daily and surfacing impacts via a unified interface for engineers, analysts, and compliance teams.[3][4]
Enterprise scale without freemium: Pay-as-you-go pricing by monitored resources suits large orgs managing hundreds of pipelines; no freemium model ensures focus on high-value, production-grade reliability, with fast profiling and audit-ready lineage for regulated industries.[1][3]
AI observability extension: Beyond traditional data quality, it detects ML/genAI input failures and drift, positioning it as the "New Relic for data" with 2025 awards like G2 top rankings and Inc. Best Workplace.[2][3][4]

Role in the Broader Tech Landscape

Monte Carlo rides the explosive growth of data-driven AI and GenAI, where 100% of data leaders face pressure to build AI but only 68% feel ready due to pervasive data downtime plaguing even top enterprises.[4] Its timing aligns perfectly with modern data stacks' complexity—proliferating warehouses, lakes, and AI pipelines—creating market forces like heightened scrutiny post-migrations (e.g., JetBlue's 16-point "Data NPS" gain) and regulatory demands for governance.[2][4][6] By consolidating metadata signals into actionable insights, it accelerates data adoption, influences the ecosystem through 400+ enterprises standardizing observability (e.g., integrations with Databricks, Snowflake), and sets the category standard its CEO defined, enabling reliable GenAI at scale amid 2025's AI maturity push.[1][2][4]

Quick Take & Future Outlook

Monte Carlo is primed to dominate as the go-to for enterprise data + AI observability, expanding beyond detection to full AI pipeline trust with faster scaling and deeper ML features.[3][4] Trends like GenAI proliferation, multi-cloud complexity, and compliance mandates will fuel growth, potentially pushing ARR past $50M+ by 2026 via wins in regulated sectors and new AI-specific modules.[1][2] Its influence will evolve from niche reliability fixer to ecosystem enabler, powering more trusted AI outcomes at Fortune 500 scale and cementing its role in making data downtime obsolete—just as it started by naming the problem.

Sources

Frequently Asked Questions

How much funding has Monte Carlo raised?

Monte Carlo has raised $241.0M in total across 4 funding rounds.

Who are Monte Carlo's investors?

Monte Carlo's investors include Accel, AirAngels, Andreessen Horowitz, Aya, B Capital Group, Cedar Capital Group, Cornerstone Venture Partners, Craft Ventures, CRV, Cyberstarts VC, Felicis Ventures, Greylock.