01 / capability
Canonical entity and relationship graphs
Defined as an explicit contract so operators can review it before it runs.
Knowledge & context · Concept
Make the knowledge answerable.
A graph-native intelligence operating platform for representing, analyzing and acting on interconnected organizational knowledge.
01
What it is
GraphNative AI is built for Enterprise architects, data and AI teams, knowledge platform operators.
The problem
GraphNative AI replaces siloed enterprise search, basic RAG systems and disconnected knowledge management layers.
The approach
A graph-native intelligence operating platform for representing, analyzing and acting on interconnected organizational knowledge.
The boundary
Work stays inside an explicit scope: named sources, defined permissions, bounded execution, retained evidence.
02
Capabilities
Five contracts the product is specified around. Each one is a boundary as much as a feature.
02 / capability
Graph-based context retrieval
Available through the product surface and the machine interfaces, with permission attached.
03 / capability
Provenance-aware intelligence
Defined as an explicit contract so operators can review it before it runs.
04 / capability
Semantic reasoning and orchestration interfaces
Defined as an explicit contract so operators can review it before it runs.
05 / capability
Graph analytics, API and MCP access
Available through the product surface and the machine interfaces, with permission attached.
03
How it works
The same three steps apply whether a person or an agent is driving.
01
Define the scope
Start from the boundary GraphNative AI is allowed to act inside: the workspace, the sources, the budget, the authority.
02
Connect the surfaces
Expose the same capability through the interface a human uses and the interface an agent calls, with one permission model.
03
Act with evidence
Every action leaves a record that can be inspected, replayed and challenged before the next one runs.
Read the specification before you believe the category.
GraphNative AI is documented as a concept: requirements, interfaces and evidence expectations. It is not presented as a live service.