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Universal Semantic Layer : The foundation for instant, actionable, agentic analytics
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Single Source of Truth

One view across your data.
One truth for everything
built on it.

One semantic foundation across disconnected data sources—unified view, shared meaning, one truth for every dashboard, notebook, LLM and agent.

Quick Read

  • One unified view across your entire data estate
  • A shared understanding of your business data
  • Clear, consistent language across teams and system
  • One shared semantic context powering AI and BI
Single source of truth 4

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Universal Semantic Layer that powers every Agent, Chatbot & Dashboard

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The Gap Between Data and Consumption

Enterprise data is abundant. But without a shared foundation, it reaches teams, BI tools and AI models in ways that distort, contradict and mislead

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    Data lives across platforms without a single, connected view

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    Business meaning is defined separately inside different tools and workflows

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    Technical structures don’t easily translate into clear business language

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    AI and BI rely on different interpretations of the same information

One logical view across your data estate

Kyvos establishes a single source of truth by logically unifying data across all your tools and teams

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    Data remains in existing warehouses and lakehouses

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    No copying or consolidating data into a new platform

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    No re-modeling required inside each tool

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    All your data appears as one connected enterprise view

One shared meaning of your data

Standardize enterprise meaning and context once—and power everything from the same semantic authority

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    KPIs and business concepts interpreted identically across workflows

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    Semantic updates propagate automatically to models, agents and reports

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    One logical layer behind every reasoning, analysis and reporting

One shared business vocabulary

Clear, business-friendly language that connects enterprise data to real-world use cases

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    A governed, shared data language for consistent, trusted analytics

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    Eliminates translation gaps between data engineers and business users

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    Business-friendly semantic abstraction over raw tables

One layer for both AI and BI

AI systems and BI tools using the same business context from the start

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    Agents, chatbots and dashboards query the same semantic layer

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    No independent data preparation pipelines for workflows

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    Consistent context and meaning across use cases

How Kyvos Fits in Your
Analytics Stack

How Kyvos Delivers a Single Source of Truth

  • Unified Semantic Data Model

    Creates one logical enterprise view across distributed data platforms

    Unified Semantic Data Model

  • Full API Support

    Exposes the centralized semantic layer to applications and AI systems

    Full API Support

  • Centralized Semantic Layer

    Defines metrics, dimensions, hierarchies and relationships once and manages them in one place

    Centralized Semantic Layer

  • Hierarchy Management

    Centrally defines enterprise hierarchies to ensure consistent rollups and aggregations across all analytics

    Hierarchy Management

  • Logical Modeling Across Data Platforms

    Builds a shared business view without moving or consolidating data

    Logical Modeling Across Data Platforms

  • Semantic Model Version Control

    Controls changes to semantic definitions to preserve consistency as the model evolves

    Semantic Model Version Control

  • Shared Calculation Engine

    Ensures consistent metric computation across BI and AI use cases

    Shared Calculation Engine

  • Metadata Management

    Centralizes business and technical metadata to maintain a shared understanding of data

    Metadata Management

FAQs

What does a single source of truth mean in enterprise analytics?
A single source of truth means every team, tool and platform works from the same business definitions—same metrics, same hierarchies, same logic. There is no reconciliation because there is no divergence.
How does Kyvos create a single source of truth?
Kyvos builds and deploys a unified semantic data model across distributed data platforms. Business logic is defined once in that model and shared with every BI tool, AI agent and application that connects to it—without moving or replicating data.
Does creating a single source of truth require data consolidation?
No. Kyvos establishes consistency logically, not physically. Your data remains in existing warehouses and lakehouses while the semantic layer unifies definitions across them.
How is this different from centralizing data in a warehouse?
Centralizing data solves storage, not meaning. Teams can still define metrics differently even from the same warehouse. Kyvos solves the semantic layer—ensuring business logic is consistent regardless of where data lives or which tool is querying it.
Does this work for both BI and AI use cases?
Yes. BI tools and AI agents connect to the same semantic foundation, so dashboards, forecasts reports and AI-generated insights all reflect the same definitions and calculations.
What happens when business definitions change?
Changes are made centrally in the semantic model. Updates propagate logically across use cases, avoiding duplicated effort and eliminating the need for enterprise-wide rework.
Can a single source of truth scale as the organization grows?
Yes. New datasets, domains and systems connect to the existing semantic model, inheriting established definitions and hierarchies without introducing fragmentation.
Does this require replacing our existing data infrastructure?
No. Kyvos overlays your existing warehouses and lakehouses. Your infrastructure stays intact; Kyvos unifies the meaning on top of it.

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Semantic Layer for AI & BI?

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