TL;DR — Cube joins Snowflake to participate as a launch partner in a new industry initiative to define an Open Semantic Interchange (OSI): an open-source, vendor-agnostic specification for describing and exchanging semantic models. Our goal is to help customers move definitions of metrics, dimensions, and business logic safely and consistently across tools thereby accelerating AI/BI adoption while preserving choice.

Why this matters

Organizations today run analytics and AI across a mosaic of platforms—data clouds, transformation frameworks, BI tools, notebooks, and AI agents. The business meaning of data (metrics, dimensions, relationships, access policies) too often gets re-implemented differently in each place, creating inconsistency and friction.

The Open Semantic Interchange (OSI) initiative aims to change that by establishing:

  • A common, open specification for semantic metadata—portable across vendors and tools.

  • Open-source code modules that translate one party’s semantic model into another’s, making interoperability practical, not aspirational.

  • A collaborative consortium focused on vendor neutrality, efficiency for data teams, and faster, more reliable AI/BI outcomes.

For customers, standardized semantics mean fewer rewrites, simpler governance, and greater freedom to choose the best tools for each job without losing the meaning of their data.

Cube’s role

Cube exists to make governed, reusable semantics available everywhere. As a launch participant in OSI, we plan to:

  1. Contribute to the OSI specification with learnings from our work powering semantic layers at scale across the Snowflake ecosystem and beyond.

  2. Provide open adapters/translation modules to read and write OSI from Cube, enabling customers and partners to move models and metrics definitions between Cube and other OSI-compatible systems.

  3. Champion interoperability for AI by making OSI semantics addressable by AI applications and agents, improving accuracy and governance for LLM-powered analytics.

What customers can expect

  • Interoperability by design. Define a metric once and use it in multiple tools via Cube’s world class APIs with consistent results. Synchronize it to other platforms like Snowflake Semantic Views as desired.

  • Operational efficiency. Reduce duplicate model work, simplify migrations, and streamline semantic governance.

  • Vendor flexibility. Adopt new AI/BI tools—or consolidate existing ones—without starting semantic modeling from scratch.

Timeline and what’s next

As materials, repositories, and other resources go live, we’ll update this post with links and add technical guidance for Cube users and partners.

If you’d like to learn more about the open semantic interchange with Cube please reach out via our contact us form.

A note of thanks

We appreciate Snowflake’s leadership in convening this cross-industry effort and are excited to collaborate with fellow launch participants. Standardized, open semantics are a win for customers, partners, and the broader data and AI community and we’re proud to help build them.