Apache Ossie (incubating) is the
universal standard for semantic data
Apache Ossie (incubating) is an industry-wide specification effort to standardize how we exchange semantic metadata across analytics, AI and BI platforms, providing a vendor neutral, single source of truth for semantic data. Ossie was previously known as Open Semantic Interchange (OSI).
AI Ready Semantic Context
Write Once, Query Anywhere.
Stop redefining "Revenue" in every dashboard. Apache Ossie uses a declarative YAML standard to define metrics, dimensions, and joins — so every tool and agent in your stack works from the same source of truth.
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Consistent Definitions
Ensure Marketing, Finance, and Sales all see the same numbers — no more metric drift.
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AI-Ready Context
Give LLMs the semantic context they need to answer business questions accurately.
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No Lock-In
Move your business logic between platforms freely. Your metrics belong to you.
semantic_model: - name: ecommerce_analytics description: ai_context: instructions: datasets: - name: orders source: sales.public.orders primary_key: [order_id] fields: - name: order_date dimension: is_time: true metrics: - name: total_revenue expression: dialects: - dialect: ANSI_SQL expression: SUM(orders.amount)
About Apache Ossie
Apache Ossie is a collaborative, open-source effort dedicated to standardizing and streamlining semantic model definitions across the data analytics, AI, and BI ecosystem.
Interoperability
Seamlessly exchange semantic models between AI agents, BI platforms, and analytics tools.
Consistency
Maintain consistent data definitions and values across every platform in your ecosystem.
Vendor-Agnostic
A common standard that works across all vendors, eliminating tool-specific inconsistencies and lock-in.
Efficiency
Reduce engineering debt and accelerate innovation by using a unified, governed semantic foundation.
The Challenge Semantic Fragmentation
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Metric Drift Inconsistent KPIs across different dashboards.
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Manual Translation Costly, error-prone reconciliation efforts.
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Hallucinations Unreliable AI grounding from conflicting data logic.
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Integration Debt Complex N-to-N custom integrations between proprietary tools.
The Solution A Unified Standard
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Single Source of Truth Unified semantic and metric definitions.
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Native Interoperability Direct exchange between platforms and AI agents.
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Trusted AI Grounding Agents reasoning accurately based on business logic.
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Reduced TCO Lower costs through automated model exchange.
Core Classes
The Apache Ossie specification defines these building blocks:
Semantic Model
Top-level container representing a complete model with datasets, relationships, and metrics.
Datasets
Logical business entities — fact and dimension tables with fields and structure.
Fields
Row-level attributes for grouping, filtering, and metric expressions.
Metrics
Aggregate calculations — sums, averages, ratios — spanning multiple datasets.
Dimensions
Categorical attributes: Where, When, Who.
Relationships
Foreign key constraints connecting datasets, supporting simple and composite keys.
Latest Updates
News and announcements from the Apache Ossie community
August 12, 2026
Kyvos Joins the Apache Ossie Ecosystem
Kyvos brings its high-performance semantic layer to the open ecosystem, helping enterprises make governed business context available to AI agents and applications - fast, accurately and at scale.
June 4, 2026
The FSI Semantic Working Group Is Live
The Financial Services Semantic Working Group has held its first formal meeting, bringing together practitioners from across banking, insurance, asset management, and market infrastructure to solve the industry's semantic alignment challenge.