Be the first to know when data breaks.

Stop bad data in its tracks – before it affects the business.

Trusted by the data teams at

  • Sofi
  • Opentable
  • Pepsi Co
  • JetBlue
  • CNN
  • Affirm
  • Fox
  • Shutterstock
  • MasterClass
  • Gusto
  • HubSpot
  • Payjoy
  • Gitlab
  • Vizio
  • Sonos
  • Toast
  • Weights & Biases
  • Prefect
  • Credit Karma
  • Mercado Libre
  • Seatgeek

Mitigate the risk and impact of bad data instantly.

Monte Carlo deploys in minutes, detecting freshness, volume, and schema incidents out-of-the-box.

Make data reliable and trustworthy.

Monte Carlo provides end-to-end coverage across your data stack for more productive data teams and happier stakeholders.

Reduce time and resources spent on data quality.

Reduce the amount of time and money spent on data quality issues with automatic detection, resolution, and prevention of incidents.

Detect issues wherever they occur.

Data quality monitoring and alerting across your entire data stack, from ingestion in the warehouse to the business intelligence layer. We’ve got you covered.

Integrate with your entire data stack.

Trusted data teams have trusted data. Monte Carlo monitors and alerts for freshness, volume, and schema changes with automated, out-of-the-box coverage in minutes.

“Within minutes of deploying Monte Carlo, my team was up and running, and we had full visibility into our data pipelines, from ingestion in BigQuery to analytics in our Looker dashboards.”

Rick Saporta Former Head of Data Strategy and Insights

“We wanted something that would effectively get this off the ground and running without us having to put in that effort. The schema, volume, and freshness checks that Monte Carlo offers delivers on that.”

Edward Kent Principal Developer

Within minutes, we were up and running with Monte Carlo and within days, the platform was uncovering critical schema and pipeline changes that would have impacted the business if left undetected”

Matt Frazier Chief Analytics Officer

Gain confidence in your production tables.

Monte Carlo’s machine learning monitors are automatically deployed across production tables. They evaluate freshness, volume, and schema changes within 2 weeks—without manual configuration or thresholding.

Custom data quality monitoring in minutes.

For your most critical fields and tables, deploy machine learning-powered monitors to evaluate 50+ metrics or create custom tests for known issues and business rules with just a few clicks or programmatically as code.

Route notifications directly to your data team.

Related data issues are automatically grouped into a single notification, delivered to Slack, Team, Jira, or wherever your team works. Grouped notifications limit white noise and ensure your team and affected data owners and dashboard users are in the loop.