Monte Carlo, a pioneer in data observability, has introduced Agent Observability, a groundbreaking capability that provides end-to-end visibility across the data and AI stack. Launched on September 9, 2025, this solution empowers data and AI teams to detect, triage, and resolve reliability issues, ensuring trustworthy AI outputs and preventing costly downtime.
Monte Carlo’s Agent Observability marks the evolution of data observability into data and AI observability, making it the first platform to unify visibility across both domains. This capability addresses the critical need for reliable AI systems, as 80% of organizations have adopted AI agents, yet 30% of AI initiatives fail due to data quality issues, according to Gartner. “For data and AI teams, reliability isn’t a ‘nice to have,’ it’s the foundation for building scalable, adopted, revenue-driving AI products,” said Barr Moses, co-founder and CEO of Monte Carlo.
Unlike point solutions that monitor either data inputs or model outputs, Agent Observability provides comprehensive oversight from data ingestion to AI responses. It includes low-code evaluations to detect issues like irrelevant outputs, declines in clarity, or task failures. “BARC research finds that more than 40% of companies don’t trust the outputs of their AI/ML models,” said Kevin Petrie, VP of Research at BARC U.S. “To make AI safe, they must extend their data governance programs to mitigate the new risks of models and agents, with a focus on responsible outputs.” Monte Carlo’s platform enables teams to set custom criteria and receive automatic alerts for underperforming AI agents.
Agent Observability enhances troubleshooting with built-in telemetry, tracking prompts, completions, latency, and errors. All data remains within the customer’s infrastructure, ensuring security and transparency. This allows teams to quickly identify and resolve issues, minimizing downtime. “When AI agents fail, the consequences are massive and long-standing: low adoption of costly and time-consuming work, erosion of customer trust, and a huge hit to the bottom line of the business,” Moses added, emphasizing the platform’s role in maintaining AI reliability.
Recognized by Forbes as the “New Relic for data” and rated #1 by G2, Gartner Peer Reviews, and ISG, Monte Carlo continues to lead with its innovative approach. Agent Observability supports enterprises like NASDAQ, Honeywell, and Roche, ensuring their AI systems deliver consistent, trustworthy results. This launch solidifies Monte Carlo’s vision of a unified data and AI observability ecosystem, setting a new standard for enterprise AI reliability.
Monte Carlo created the data + AI observability category to help enterprises drive mission critical business initiatives with trusted data + AI. NASDAQ, Honeywell, Roche, and hundreds of other data teams rely on Monte Carlo to detect and resolve data + AI issues at scale. Named a “New Relic for data” by Forbes, Monte Carlo is rated as the #1 data + AI observability solution by G2 Crowd, Gartner Peer Reviews, GigaOm, ISG, and others.
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