The AI Visibility, Authority & Growth Intelligence Platform for Real Estate
AuthoritySignal shows how AI understands, cites, and surfaces real estate professionals, then connects provider observations to durable authority evidence, identity, and public sources.
Core organizational intelligence follows Professional → Office → Region. Team and enterprise workspaces are separate configured views, not a claim of true team-level scoring or a national hierarchy.
AuthoritySignal is a live platform; public pages do not publish unsupported user, office, agent, or regional scale estimates.
A live real-estate authority intelligence platform.
AuthoritySignal connects AI discovery, evidence, competitive intelligence, authority-building, digital infrastructure, and lead opportunities across professionals, listings, offices, regions, and enterprise organizations.
AuthoritySignal measures how AI systems understand and surface a professional or organization. It connects those observations to verified public authority evidence, identifies supportable improvements, helps publish approved authority information, supports opportunity capture where deployed, and measures change over time.
The broader operating model is Measure → Diagnose → Improve → Publish → Convert → Verify. Publish and convert steps depend on approved content, deployed public surfaces, permissions, and available lead records.
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.
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.
AuthoritySignal publishes authoritative conclusions only when the available evidence clears the required standard. Insufficient evidence remains unknown rather than becoming false certainty. Durable authority evidence forms the base; time-stamped provider observations are bounded signals, not a license for one response to dominate the score.
The platform resolves professional identity and consistency across important public business details and distinguishes first-party assertions from independently corroborated evidence.
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.
Observe → Understand → Diagnose → Improve → Verify. Actions are personalized to profile, gaps, freshness, geography, niche, and opportunity; completing one does not prove it caused a later provider recommendation.
AuthoritySignal can remeasure supported visibility and evidence after meaningful changes so customers can see what changed over time. Independent AI systems remain outside AuthoritySignal's control, so results are reported as observations rather than guaranteed or causal outcomes. Lifecycle: Measure again → compare supported evidence → report what changed.
For live AI visibility measurement, AuthoritySignal supports configured integrations across major AI providers including OpenAI / ChatGPT, Perplexity, Anthropic / Claude, and Google Gemini. Availability depends on the configured integration and observation context.
Provider behavior remains independent: AuthoritySignal does not guarantee an AI recommendation or claim that an action caused one.
LIVE / PROVEN capabilities: Multi-provider AI visibility measurement and evidence-gated diagnostics; Competitive Intelligence and supported authority comparisons where qualifying evidence exists; Remeasurement and verification of supported visibility and evidence changes; Authority & Evidence Intelligence, Authority Hub workflows, and approved Public Authority Profiles; Recruiting intelligence, office reports, and organization visibility where configured; Campaign Center content activation across supported authority-building formats; Listing Visibility and Property Intelligence, including Property Strategy Reports; Hosted property landing pages with consumer inquiry capture
CONTROLLED BETA / ENTERPRISE PILOT capabilities where deployed: Selected brokerage or regional web experiences where deployed; Selected enterprise data and property integrations where deployed; Expanded recruiting and consumer opportunity routing where deployed
LIVE / PROVEN — ENTERPRISE-MANAGED capabilities where configured: Authority Refresh / AI Discovery Refresh is available through the enterprise platform where configured. It helps publish approved authority updates and verify rediscovery or later observations where supported. AuthoritySignal does not control independent crawlers or AI systems and does not guarantee a recrawl, recommendation, or model update.
ROADMAP: Additional self-serve guidance, automation, and integration capabilities will be announced when supported and verified.
RE/MAX of Southeastern Michigan has completed a full regional rollout and implementation of AuthoritySignal AI across the regional organization. AuthoritySignal serves as its regional AI visibility and authority intelligence platform, supporting the region, its offices, and real estate professionals.
This regional implementation is with RE/MAX of Southeastern Michigan and does not represent or imply national adoption or endorsement by RE/MAX LLC. Deployment status is distinct from outcome measurement; unsupported scale figures are not published on this public surface.
How AuthoritySignal works
AuthoritySignal evaluates public entity, trust, authority, local-relevance, and content-consistency signals, then provides an AI Visibility Score and prioritized guidance for improvement.
Current flagship research: AI Discovery in Real Estate
AuthoritySignal Research published a three-round study with 1,440 analytical observations: 15 professionals, five U.S. markets, four providers, and eight query families.
No observations met the study's normalized recommended classification during these three rounds: 0 of 1,440 analytical observations. The study is descriptive, cohort-limited, and does not claim long-term stability or population-level inference.