Snowflake, together with partners, is introducing the open-source initiative ‘Open Semantic Interchange’ (OSI). The initiative aims to create a standard for semantic metadata in AI and BI applications.
The problem is ubiquitous in the modern data world. Every tool interprets business statistics differently, leading to confusion and undermining trust in AI-driven insights. As AI transforms the way companies use data, this challenge is only growing.
Strong coalition of parties
The initiative has attracted significant support from the industry. In addition to Snowflake as the initiator, more than 15 parties have joined, including Alation, Atlan, BlackRock, Blue Yonder, Cube, dbt Labs, Elementum AI, Hex, Honeydew, Mistral AI, Omni, RelationalAI, Salesforce, Select Star, Sigma, and ThoughtSpot.
This broad support marks a clear break with closed, single-vendor approaches. Instead, market players are opting for a future based on interoperability and open source collaboration.
Finally, a solution to semantic chaos
The OSI initiative addresses a fundamental problem. Data and AI teams often spend weeks reconciling conflicting definitions between different platforms. This overhead hinders innovation and significantly slows down the adoption of AI applications.
The vendor-neutral specification introduced by OSI should ensure that all tools speak the same language. This provides organizations with the flexibility to utilize best-of-breed technologies without compromising consistency.
The initiative focuses on three main objectives. First, improving interoperability between tools and platforms in a fragmented data landscape. Second, accelerating AI and BI adoption through consistent semantics that support trust. Third, streamlining processes through a shared specification that reduces overhead.
Practical impact for organizations
The diversity of participants, from traditional data platforms to AI startups, shows that the problem affects all segments of the market. This creates momentum for broad adoption of the standard.
For companies, OSI means that semantic data becomes interoperable and reliable across platforms. Teams can focus on innovation instead of solving compatibility issues between different tools.
This is particularly relevant now that many organizations are struggling to scale AI and BI because inconsistent semantics undermine trust. By standardizing how semantics are defined and exchanged, OSI ensures that data is managed, consistent, and rich in context.
The initiative thus lays the foundation for reliable and scalable AI adoption, potentially unlocking the next wave of innovation in data-driven organizations. As more parties join, the likelihood that OSI will become the industry standard that is so desperately needed is increasing.