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Monte Carlo’s low-code observability solution lets users apply custom prompts and AI-powered checks to unstructured fields, to monitor for the quality metrics that are relevant to their unique use case

May 30, 2025 //  by Finnovate

Monte Carlo has launched unstructured data monitoring, a new capability that enables organizations to ensure trust in their unstructured data assets across documents, chat logs, images, and more, all without needing to write a single line of SQL. With its latest release, Monte Carlo becomes the first data + AI observability platform to provide AI-powered support for monitoring both structured and unstructured data types. Monte Carlo users can now apply customizable, AI-powered checks to unstructured fields, allowing users to monitor for the quality metrics that are relevant to their unique use case. Monte Carlo goes beyond the standard quality metrics and allows customers to use custom prompts and classifications so as to make monitoring truly meaningful. Monte Carlo continues its strategic partnership with Snowflake, the AI Data Cloud company, to support Snowflake Cortex Agents, Snowflake’s AI-powered agents that orchestrate across structured and unstructured data to provide more reliable AI-driven decisions. In addition, Monte Carlo is extending its partnership with Databricks to include observability for Databricks AI/BI – a compound AI system built into Databricks’ platform that generates rich insights from across the data + AI lifecycle – including ETL pipelines, lineage, and other queries. By supporting Snowflake Cortex Agents and Databricks AI/BI, Monte Carlo helps data teams ensure their foundational data is reliable and trustworthy enough to support real-time business insights driven by AI.

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Category: Data Economy & Privacy, Innovation Topics

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