Give Your Data a Shared Business Meaning

Raw tables are just numbers until your team defines what they mean. Linearvis Business Ontology lets you model your business objects, map data sources to them, and make that shared vocabulary active in every AI workflow.

The Problem: Every team speaks a different data language

Analysts query the same column with different names and get different answers
AI models make predictions without knowing what the data represents in your business
Governance and compliance rules can't enforce policies they don't understand
New team members spend weeks learning which tables map to which business concepts

The Solution: One shared business model that every layer references

Linearvis Business Ontology lets you define your business objects once, map data sources to them, and make that model active in AI context so Leo, predictions, rules, and summaries all reason over the same vocabulary.

Business Object Modeling Define your key entities — customers, products, transactions — with properties and descriptions

Data Source Mapping Bind columns from any connected data source to your business object properties

Ownership & Stewardship Assign data owners and stewards per object for clear accountability

Relationship Graph Draw relationships between objects and visualise the full business model as a graph

Data Quality Scoring Automatic per-property quality scores with AI-suggested remediation steps

Active in AI Context Confirmed objects are injected into Leo, predictions, rules, and summaries as shared context

Get Started

Linearvis is free to try. Upload your first dataset and get AI-powered dashboards, insights, and predictions in minutes.

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