dbt Labs Takes Bold Step in AI with Open Sourcing MetricFlow at Coalesce 2025

In a pivotal announcement made at the annual Coalesce 2025 conference, dbt Labs, renowned for setting standards in AI-ready structured data, conveyed its commitment to fostering open semantic interchange by open sourcing MetricFlow under the Apache 2.0 license. This strategic shift not only signifies dbt Labs' dedication to advancing trustworthy AI for enterprises but also emphasizes the company's role as a pivotal player in the Open Semantic Interchange (OSI) initiative, a collaborative effort among industry leaders to establish neutral standards for semantic data exchange across various analytics platforms and AI tools.

As enterprises race towards implementing AI, they often encounter challenges stemming from inconsistent metrics and fragmented definitions. These issues hinder trust and slow down broad adoption, creating an urgent demand for a unified standard that facilitates reliable metrics across diverse tools. MetricFlow serves as the foundational engine that compiles metric definitions into code, ensuring that the computation of these metrics is both explainable and reliable—unlike traditional text-to-SQL methods, which can lack transparency.

Driving Governance for AI-Ready Data

Following the acquisition of Transform in 2023, dbt Labs integrated MetricFlow into its Semantic Layer. This innovative tool utilizes semantic model information and metric YAML configurations to build and execute SQL within users' data platforms, thus providing governed metrics. By making MetricFlow open-source, dbt Labs empowers stakeholders with a transparent and extensible engine. This move aims to enable AI agents to rely on trusted metric definitions, thereby facilitating consistent results across varied tools and cloud environments at scale.

"dbt is rooted in our open-source DNA. Transitioning to open-source MetricFlow will unlock tremendous opportunities for data practitioners to drive significant value within their organizations," remarked Ryan Segar, Chief Product Officer of dbt Labs. The alarming reality is that with 90% of analysts indicating a critical need for more efficient tools to meet their business demands, the open-sourcing of this engine addresses the pervasive metric drift that can erode trust and efficiency across organizations.

Standardizing Fragmented Data Across Industries

dbt Labs' commitment to the OSI initiative, spearheaded by prominent players such as Snowflake and Salesforce, is aimed at combating the costly ramifications of non-standardized data definitions. In this context, Josh Klahr, Director of Analytics Product Management at Snowflake, highlighted the importance of standardizing semantic metadata for effective AI adoption. "The OSI initiative aspires to create unified definitions and sharing methods for semantic metadata, and dbt Labs’ transition to the Apache 2.0 license for MetricFlow is a significant stride towards this goal," Klahr explained.

The OSI seeks to address the drawbacks associated with proprietary semantic standards by providing solutions that directly target the bottlenecks preventing organizations from realizing their ambitious AI objectives. By situating MetricFlow as a core element of this initiative, dbt Labs positions itself as an integral part of moving towards a reliable and shared analytic metadata framework that can catalyze better trust in data utilization.

Rob Vicker, Data Analytics Architecture Director at EMS Insurance, emphasized the critical nature of defining metrics within MetricFlow for establishing a consistent source of truth. He pointed out that various BI and AI tools frequently interpret metrics differently, which can result in inefficiencies. However, he believes that by leveraging open-source MetricFlow, the OSI can guarantee uniformity in how metrics are utilized across different tools. This not only saves analysts considerable time but also streamlines the auditing process and allows users flexibility in accessing data without the hindrance of frequent code updates.

Conclusion

With the transition towards open-source MetricFlow, dbt Labs is making a significant contribution to the ongoing dialogue about standardization in data management and analytics. This initiative highlights the importance of collaboration among industry stakeholders to build a more robust framework for achieving trustworthy and scalable AI solutions. As a result, organizations can enhance their decision-making processes, leverage data in a more reliable manner, and ultimately drive greater efficiency and insight across their operations.

For more updates on MetricFlow and dbt Labs’ initiatives, visit getdbt.com. Follow dbt Labs on their social platforms to stay informed on upcoming developments.