Barr Moses

Leading Monte Carlo

Barr Moses is co-founder and chief executive of Monte Carlo, a company known for creating the data observability category. Monte Carlo now describes itself as an AI and data observability company that helps enterprises trust their AI agents in production, by monitoring and troubleshooting both the agents and the data pipelines behind them. Its stated mission is to enable the world's enterprises to adopt trusted AI.^[1][3]

The company's own site cites more than 400 enterprise customers, about 1,000 incidents resolved each day and some 10 million tables monitored. Those are company-reported figures.^[1]

Moses co-founded the company with Lior Gavish, and Redpoint Ventures, which partnered with Monte Carlo on its 2021 Series B, lists the two as founders. Redpoint quotes the company's aim as accelerating the world's adoption of data by reducing what it calls data downtime.^[4]

Before Monte Carlo

Moses served in the Israeli Air Force, where she commanded a unit of intelligence data analysts. She holds a bachelor's degree in mathematical and computational science from Stanford.^[3]

She then worked as a management consultant at Bain & Company and as vice president of customer operations at Gainsight, the customer success software company, before starting Monte Carlo.^[3]

On an Accel podcast she recalls that in 2018 she was looking to start a company and pursuing several ideas at once, and that the one she identified as data downtime became the foundation of Monte Carlo after customer conversations confirmed the demand. The episode also covers raising the seed round with a weak slide deck and winning the first customers.^[5]

Naming a category

Thoughtworks credits Moses with establishing data observability as a product category. The idea at the center of the early pitch was what she calls data downtime, a concept the Accel interview traces back to the company's origin.^[3][5]

She is a co-author of the O'Reilly book Data Quality Fundamentals: Building Reliable Data Pipelines, which Thoughtworks lists in her profile.^[3]

In the Accel interview she also discusses why competition in a new category helps the company that created it, how she looks for risk-takers when hiring, and how her leadership style changed as the company grew.^[5]

Funding and growth

On May 24, 2022 Monte Carlo announced a $135 million Series D led by IVP at a $1.6 billion valuation, bringing total funding to $236 million. Accel, GGV Capital, Redpoint Ventures, ICONIQ Growth, Salesforce Ventures and GIC Singapore took part.^[2]

At the time of that round, the company said headcount had grown sixfold over twenty months to 120 people, that revenue had more than doubled every quarter since its Series C announcement in August 2021, and that customer retention in 2021 was 100 percent. Customers named in the release included JetBlue, Affirm, CNN, MasterClass, Auth0 and SoFi.^[2]

Moses framed the market argument as a matter of trust: having data is not enough, she said, because it also has to be discoverable, accessible and reliable.^[2]

The move to AI agents

On September 9, 2025 Monte Carlo announced Agent Observability, a product that monitors AI agents in production and traces problems back to their data sources. The company says it is the first vendor to unify observability across data and AI in one platform.^[6]

The release describes output quality checks that use an LLM as judge or deterministic evaluations, low-code evaluations that flag declining relevance or helpfulness and unfinished tasks, and telemetry covering prompts, completions, user queries, latency and errors for root-cause analysis. Telemetry is stored in the customer's own warehouse, lakehouse or lake, so sensitive tracing data stays within the customer's infrastructure.^[6]

In the announcement Moses argued that reliability is the foundation for AI products that can scale, win adoption and generate revenue, rather than an optional extra.^[6]

Why she matters

Moses is one of the founders who turned a practitioner's complaint, broken dashboards and untrustworthy data, into a named software category with its own buyers and budget line. Monte Carlo's funding rounds, named enterprise customers and a book on the discipline show how far that category has travelled.^[2][3][4]

Her current bet is that the same reliability problem returns, with higher stakes, when companies put AI agents into production. The September 2025 launch makes Monte Carlo a test of whether data observability can become the foundation for AI observability.^[1][6]

On The Executive List

Barr Moses is ranked No. 93 on The Executive List (October 2026) in the Chief Data Officers discipline. The ranking reflects The Executive Review's own editorial Trending Score; it is not an outside award, and placement on the list is never sold. View the October 2026 edition.