Semantic Substrate

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The graph-layer position for attribution on the agent-era TLD.

Attribution as a connected graph — the canonical coordinate for systems that map causal relationships, credit flows, and provenance chains as structured data.

Coordinated sets this position belongs to — the coverage it extends. Counts are the live cluster size in the graph.

Primary home

Attribution cluster357

Also appears in

Graph cluster46

Architectural context

Attribution · Cross-Vertical · 2 compound moats. Architectural surface: Attribution. Cross-cutting: Graph.

Layer position: Substrate (L1)

AttributionGraph

Why this is canonical

'Graph' is the technical substrate that makes attribution tractable at scale: knowledge graphs, provenance graphs, causal graphs, and citation graphs are all forms of attribution graphs. On .ai, this string occupies the data-structure layer of the attribution substrate — the natural home for systems that model attribution as relationships between entities, not just as a list of credits or a log of events.

Where it fits

A few directions this coordinate opens —

AI provenance graph
A structured graph of AI model lineage, training-data attribution, and output provenance — enabling traversal, querying, and auditing of AI credit chains.
AI infrastructure companies, model audit platforms, knowledge graph builders
Marketing attribution graph
A graph-based attribution model mapping the full causal chain from touchpoints to conversions — enabling sophisticated multi-path analysis.
MarTech platforms, advanced analytics infrastructure, causal AI companies

Illustrative, not exhaustive — held as a transferable canonical position, open to the buyer's own use.

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