New capabilities bring observability to unstructured data—no SQL required

Monte Carlo, the leading data + AI observability platform, has launched unstructured data monitoring—a new capability allowing organizations to monitor and ensure trust in assets like documents, chat logs, images, and more, all without writing SQL.

According to IDC, 90% of enterprise data is unstructured, yet many organizations lack visibility into its quality. Monte Carlo is the first platform to bridge this gap by extending observability to both structured and unstructured data types with AI-powered monitoring.

Observability for the Next Generation of Data + AI Products

As generative AI advances, unstructured data has become essential to powering analytics, decision-making, and AI applications. Monte Carlo now enables users to apply AI-driven, customizable checks to unstructured fields, supporting a wide range of quality metrics tailored to each use case. Users can also create custom prompts and classifications to enhance relevance and impact.

Example use cases include:

  • Flagging texts or images missing critical details
  • Alerting on customer sentiment drift in service transcripts
  • Validating AI-generated outputs for tone, structure, or accuracy
  • Identifying off-topic or irrelevant content via classification

This monitoring capability is fully integrated into Monte Carlo’s existing engine and deployable with just a few clicks.

Supported platforms include Snowflake, Databricks, and BigQuery, with native integration into each platform’s LLM or AI function libraries, ensuring sensitive data remains within customer environments.

“Enterprises aren’t just building AI—they’re racing to build AI they can trust,” said Lior Gavish, co-founder and CTO of Monte Carlo. “High-quality unstructured data—like customer feedback, support tickets, or internal documentation—isn’t just important; it’s foundational to building powerful, reliable AI.”

This release reinforces Monte Carlo’s broader mission to offer end-to-end observability across the full data + AI lifecycle, evolving beyond data observability into a comprehensive AI observability platform.

Building Trust in AI Starts With AI-Ready Data

Monte Carlo has also announced new integrations to support AI observability within Snowflake Cortex Agent and Databricks AI/BI.

Supporting Snowflake Cortex Agent and Databricks AI/BI

Monte Carlo deepens its partnership with Snowflake to support Snowflake Cortex Agents, which unify structured and unstructured data for AI-driven decision-making.

Additionally, Monte Carlo’s integration with Databricks now includes observability for Databricks AI/BI—a system that extracts insights across the data + AI lifecycle, including ETL pipelines, data lineage, and queries.

“AI applications are only as powerful as the data powering them,” said Shane Murray, Head of AI at Monte Carlo. “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.”

To stay updated on the latest developments from the 2025 Snowflake Summit and Databricks Data + AI Summit, visit the Monte Carlo blog.

Planning to attend? Visit Monte Carlo at booth #1508 at the Snowflake Summit (June 2–5) or booth #F602 at the Databricks Data + AI Summit (June 9–12).

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