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Wholesale exporters from Japan   Company Established 1983
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Snowflake and Salesforce launch AI metrics standard

by Edwin O.
September 30, 2025
in Data & Analytics
Snowflake Salesforce collaboration

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Snowflake, Salesforce introduce semantic layer to unify AI business metrics

On Tuesday, Snowflake, Salesforce, and significant partners in the industry released the Open Semantic Interchange (OSI) initiative, installing a vendor-neutral architecture, in order to standardize fragmented data semantics among AI and business intelligence systems. The open-source collaboration will deal with one of the largest obstacles on the way to the adoption of AI through the creation of unified conceptualizations of business logic across tools and applications.

Industry coalition tackles fragmented data semantics challenge

According to Analytics India Magazine, Snowflake, Salesforce, BlackRock, dbt Labs, RelationalAI, and a few more partners introduced Open Semantic Exchange (OSI), an open source project that seeks to standardise data fragmented semantics across platforms and tools. The project presents a vendor-neutral semantic model specification that is aimed at establishing consistency in the definition and sharing of business logic within artificial intelligence (AI) and business intelligence (BI) applications.

Evangelical cross-company product EVP Christian Kleinerman said the work is to resolve a groundwork problem. With the open semantic exchange project, we can be proud of establishing one of the first steps, as our partners, to address one of the fundamental problems facing AI, the absence of a standard semantics. This effort likened the industry as being united, not a competition, to present solutions to common problems and create an increasingly connected, open ecosystem with and without, he responded.

Universal specification will work to do away with operational complexity

Examples of technology vendors and ecosystem players that are in support of the OSI are Alation, Atlan, Blue Yonder, Cube, Elementum AI, Hex, Honeydew, Mistral AI, Omni, Select Star, Sigma, and ThoughtSpot. The group will enhance interoperability among tools, make operations simpler, and enhance the fast-tracked introduction of AI and BI through the simplified development of a universal semantics specification.

Trust and reliability are the key tenets of major technology leaders

According to Snowflake, Southard Jones, chief product Officer of Tableau, called the initiative vital in the establishment of confidence in AI insights. By co-leading the Open Semantic exchange with Snowflake and its partners, its is establishing the core that every AI agent and BI application requires, a shared semantic framework that ensures maintainability of meaning across platforms. This is the Rosetta Stone of business data, he said.

As Chief Product Officer at dbt labs, Ryan Segar was quoted as saying the move will enable the practitioners to operate more smoothly. He believes that with the assistance of this open source initiative, data practitioners and ecosystem builders need to guarantee the consistency and reliability of data, explaining why this requires a universal language to define data. The OSI adds to this fight directly and with a concerted effort that merges the standpoint of business, domain, and industry semantics, which alone becomes vendor-neutral.

Open standards approach marks industry transformation shift

The main objectives of the program involve interoperability improvement in tools and platforms, network adoption of AI and BI applications, and simplified operation and a decrease in complexity. Organizations usually use an amalgamation of AI, BI, and analytics tools in a fragmented data area. OSI develops a common semantic base such that all tools could communicate a common language and provide companies with the room to use the best-of-breed technologies and ensure that metrics and business logic would remain consistent.

The Open Semantic Interchange is expected to be a much-needed breakthrough in the development of enterprise AI because industry leaders used to work closely to address the most critical data inconsistency issues. This joint initiative will help to spread the use of AI faster and minimize the complexity of these operations in an organization by creating universal semantic standards used by all.

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