Monte Carlo
Headquarters
San Francisco, CAFounded
2019CEO / Founder
Barr MosesEmployees
201-500Funding
Series D+ — $236MProducts
1 product listedAvg. AI Score
7.9/10Website
montecarlo.ai/
Profile updated
About Monte Carlo
Monte Carlo is a data and AI observability company that helps organizations monitor the reliability of the data and machine-learning pipelines feeding their analytics and production AI systems. It was founded in 2019 by Barr Moses, who serves as CEO, and Lior Gavish, its CTO, and is headquartered in San Francisco. The company is credited with defining the "data observability" category, applying practices from software application monitoring to data pipelines.
Its platform automatically detects data quality problems such as broken pipelines, schema changes, and anomalous values, then helps data teams trace incidents to their root cause across warehouses, lakes, and BI tools. Monte Carlo integrates with systems including Snowflake, Databricks, BigQuery, Airflow, and dbt, and has extended its coverage toward observability for AI agents and the data that powers them. It has been ranked the top data observability solution by review site G2 across multiple quarters.
Monte Carlo has raised roughly $236 million across four rounds from investors including Accel, GGV Capital, Redpoint Ventures, ICONIQ Growth, Salesforce Ventures, and GIC. Its $135 million Series D in May 2022, led by IVP, valued the company at $1.6 billion and made it the first data observability firm to reach unicorn status, following a Series C in August 2021. The company employs around 500 people.
Specialties
Financials
Dated, source-cited figures. Estimates are marked.
Products by Monte Carlo
All products by Monte Carlo reviewed by our AI panel of experts.
How Our Review Panel Scores Monte Carlo
Six independent reviewer personalities assessed Monte Carlo's product on their own terms. They landed within 0.8 points of each other, an unusually strong consensus.
Averaged across 1 reviewed product in our catalog. Scores are out of 10.
Competitive Landscape
Who Monte Carlo competes with, and how they differ.
Superconductive's Great Expectations is an open-source, code-first framework where engineers manually author "expectations" to test pipelines, versus Monte Carlo's fully-managed platform that uses ML-based anomaly detection to catch data and AI issues automatically without rule authoring.
1 product reviewed on TopReviewed
Collibra bundles data quality and observability (built on its Owl Analytics acquisition) inside a broader enterprise data governance and cataloging suite, while Monte Carlo is a dedicated observability platform focused specifically on detecting and resolving data and AI pipeline incidents.
1 product reviewed on TopReviewedBigeye is a venture-backed data observability platform now repositioning as an "AI Trust" platform for enterprise data and AI reliability, competing most directly with Monte Carlo for large-enterprise data teams evaluating specialized (non-governance-suite) observability tools.
Company Timeline
Key milestones in Monte Carlo's history, with sources.
- Launch
Launched Agent Observability
Monte Carlo launched Agent Observability, giving AI and data teams unified visibility into the reliability of AI agents.
techtarget.com - Partnership
First data+AI observability platform to launch native Salesforce integrations
Monte Carlo unveiled native integrations with Salesforce CRM and Salesforce Data Cloud, monitoring data quality and supporting Agentforce AI agents built on that data.
montecarlo.ai - Launch
Extended observability to unstructured data
Monte Carlo extended its data observability platform to cover unstructured data quality issues, beyond its original structured/tabular data focus.
siliconangle.com - Launch
Added new GenAI capabilities for enterprise data quality management
Monte Carlo announced new generative-AI features aimed at streamlining data quality management at enterprise scale.
techtarget.com - Funding
Series D — $135M led by IVP at $1.6B valuation
Monte Carlo raised $135M in a Series D led by IVP, with Accel, GGV Capital, Redpoint Ventures, ICONIQ Growth, Salesforce Ventures and GIC Singapore participating, valuing the company at $1.6B and bringing total funding to $236M.
montecarlo.ai - Funding
Series C — $60M led by ICONIQ Growth
Monte Carlo raised $60M in a Series C led by ICONIQ Growth, with Salesforce Ventures and existing investors Accel, GGV Capital and Redpoint Ventures participating, bringing total funding to date to $101M.
techcrunch.com - Funding
Series B — $25M co-led by GGV Capital and Redpoint Ventures
Monte Carlo raised a $25M Series B co-led by GGV Capital and Redpoint Ventures, with Series A lead Accel also participating.
techcrunch.com - Funding
Series A — $16M led by Accel
Monte Carlo raised $16M in a Series A round led by Accel, with participation from GGV Capital, to build what it called the world's first data reliability platform.
montecarlo.ai - Founded
Monte Carlo founded by Barr Moses and Lior Gavish
Monte Carlo was founded in 2019 by Barr Moses (CEO) and Lior Gavish (CTO) in San Francisco to build a data reliability and observability platform.
forbes.com
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