The intelligence layer that maps how AI systems understand commerce.
AI doesn't understand websites the way humans do. It understands relationships.
The AI Commerce Graph™ maps how businesses, products, trust, content, and customer intent connect inside AI systems, creating the foundation for recommendation intelligence.
Every recommendation is the result of thousands of connected signals. The AI Commerce Graph™ models those relationships so we can measure, analyze, and improve how businesses are understood by AI.
Hovering a node highlights every connected relationship. Clicking a node opens its details on the right.
Hover any node to see how it connects.
The starting point of every recommendation. AI first understands what the customer wants, then searches the graph for the most relevant businesses and products.
Every business becomes a unique entity inside the graph.
Products are the objects AI recommends.
Categories organize commerce into meaningful groups.
Mentions represent where and how businesses appear across AI-accessible content.
Trust signals help AI estimate whether a business is reliable.
The AI Commerce Graph™ is built from six entity types. Together, they form the structure AI systems search when deciding who and what to recommend.
Every business becomes a unique entity inside the graph.
The graph stores how AI identifies, understands, and connects businesses across different contexts.
Products are the objects AI recommends.
Each product carries semantic attributes that help AI understand what it is, who it is for, and when it should be recommended.
Categories organize commerce into meaningful groups.
They allow AI systems to connect similar products and businesses to relevant customer intent.
Mentions represent where and how businesses appear across AI-accessible content.
Not every mention is equal. The graph measures frequency, context, source quality, and semantic relevance.
Trust signals help AI estimate whether a business is reliable.
These signals influence confidence, not just visibility.
Recommendations are the observable output of the graph.
Every recommendation represents the combined effect of hundreds of connected signals.
Relationships matter more than individual nodes.
Customer intent is the starting point of every recommendation. AI first understands what the customer wants. Only then does it search the graph for the most relevant businesses and products.
Intent connects everything.
The AI Commerce Graph™ is continuously refined using multiple independent data sources.
Each source strengthens different parts of the graph.
It powers everything we build. It provides the underlying relationships used by:
With a graph, recommendations become measurable.
Businesses become connected.
Trust becomes visible.
Patterns become explainable.
The AI Commerce Graph™ transforms isolated observations into a structured understanding of how AI systems discover, evaluate, trust, and recommend businesses.
The AI Commerce Graph™ is continuously expanding. As new businesses, products, recommendations, and trust signals are discovered, the graph evolves alongside the AI ecosystem, providing an increasingly complete representation of how intelligent systems understand commerce.
The only node users actually see.
Discover how the AI Commerce Graph™ powers the complete AI Commerce Intelligence Framework and the products built on top of it.
Go to the Framework OverviewIllustrative example · single-site signal for atomfoundry.dev.
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