Monte Carlo named 2026 Data Governance Snowflake Product Partner of the Year. Recognition highlights Monte Carlo's data & AI observability leadership and commitment to helping enterprises run reliable AI on Snowflake SAN FRANCISCO, June 02, 2026 (GLOBE NEWSWIRE) - Monte Carlo today announced at Snowflake's annual user conference, Snowflake Summit 2026, that it has been named the 2026 Data Governance Snowflake Product Partner of the Year by Snowflake, the AI Data Cloud company. Monte Carlo was recognized for its achievements as part of the Snowflake AI Data Cloud, helping joint customers achieve the end-to-end visibility they need to run reliable AI on Snowflake, from the data powering agents, to the behavior, performance, and outputs of those agents. Together, Monte Carlo and Snowflake are empowering teams to deploy trusted AI at scale. "Agentic AI is transforming how enterprises operate - but that transformation only works if both the agents and their underly... Third-Party Content Disclaimer Content displayed on this platform may include news articles, reports, and other materials aggregated from publicly available third-party sources through automated tools. Such content is not created, written, commissioned, or edited by Straits Interactive Pte Ltd or the Data Protection Excellence (DPEX) Network. While DPEX Network take reasonable steps to ensure responsible publication, DPEX Network do not independently verify all third-party information and make no representations as to its accuracy, completeness, or reliability. The views, findings, and statements expressed in third-party content belong solely to the original source and do not reflect the views of Straits Interactive Pte Ltd or the DPEX Network. If you believe any content is inaccurate, infringing, or should be removed, please contact DPEX Network at [email protected]. DPEX Network will review the matter and, where appropriate, take action in accordance with its internal policies.

Monte Carlo has launched Agent Observability capabilities providing unified visibility across AI agent lifecycles. The platform monitors four critical pillars: context, performance, behaviour and outputs, addressing a significant gap in enterprise AI deployment. A Monte Carlo survey reveals 73% of enterprises require monitoring and alerting before deploying AI agents, yet 63.4% cite lack of observability as a top deployment barrier. Additionally, 53% of enterprises expect to significantly rebuild or redesign already-deployed AI agent systems. The platform enables teams to detect hallucinations, diagnose performance issues and validate workflow execution. Axios is using Monte Carlo to ensure accuracy in its AI-powered content tagging system, initially built with OpenAI, with plans to expand across 12 additional large language model applications.