The Authority Graph organizes evidence relationships
The Authority Graph is AuthoritySignal's proprietary relationship intelligence layer. It connects verified professional identity with relevant markets, expertise, public evidence, and authoritative sources so AuthoritySignal can produce stronger authority intelligence while preserving provenance and privacy. This is an evidence relationship model, not a claim that the product is a fully traversable graph database.
The core organizational progression is Professional → Office → Region. Team and enterprise workspaces are separate configured views; authorized rollups and drill-down depend on account setup, permissions, and data coverage.
What the graph connects
Professional and organizational relationships connect to markets, specialties, identity, evidence, sources, authority signals, AI observations, grounded actions, and verification history. Organizational intelligence is the authorized rollup and comparison layer.
The graph preserves evidence and source provenance and supports understanding of change over time where the underlying measurement exists. AuthoritySignal preserves evidence and AI observations over time so professionals and organizations can understand progress and subsequent observations without claiming that one action caused an independent AI response. It does not expose private desired-positioning inputs by default, and it does not guarantee or predict an AI recommendation.
How it relates to the other AuthoritySignal surfaces
Authority Hub is where a professional defines, understands, and strengthens an authority position. Public Authority Profiles are the approved publishing layer. The Authority Graph is the relationship and evidence layer underneath those workflows; organizational intelligence is the rollup layer for authorized leaders.
Competitive Authority Comparison is available where sufficient comparable evidence exists. It compares supported observable authority differences across broad areas such as identity, evidence, relevance, reputation, source strength, and freshness. The comparison preserves evidence limits and is not predictive, causal, or a guarantee of an AI recommendation.