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AuthoritySignal is a live platform; public pages do not publish unsupported user, office, agent, or regional scale estimates.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 diagnoses the evidence, authority, identity, local-relevance, and competitive environment behind those observations; identifies supportable improvements; helps activate those improvements through content and digital authority surfaces; captures and routes consumer, recruiting, and listing opportunities where deployed; and preserves subsequent observations so change can be measured 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.
AuthoritySignal organizes the evidence relationships surrounding a professional—identity, brokerage, market relevance, public sources, authority signals, AI observations, and improvement history—so users can understand the evidence environment AI systems are working with.
Competitive Authority Comparison is live in production. It compares supported observable evidence differences between a professional and a resolved competitor across ten authority/evidence dimensions: entity / identity clarity, affiliation consistency, local-market corroboration, specialty / expertise evidence, independent authority evidence, review / reputation evidence, citation / source diversity, content consistency, evidence freshness, public-source coverage. Where sufficient comparable evidence exists, it can identify a Biggest Supported Competitive Authority Gap. Provenance, evidence status, confidence, unknown states, ambiguous identity, unresolved competitor, and insufficient-evidence states remain visible. This is an evidence-backed comparison of observable differences that may be actionable—not a predictive or causal model, and not a guarantee that closing a gap will produce 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 NAP consistency—name, phone, brokerage, address, and website—and distinguishes a professional's own assertion from independently corroborated evidence.
AuthoritySignal preserves evidence and AI observations over time so professionals and organizations can compare identity clarity, evidence coverage, provider agreement, open gaps, and subsequent observations. Completing an action does not by itself prove it caused a later recommendation.
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.
For supported competitive-authority actions, AuthoritySignal does not stop at recommendations. The platform preserves what was recommended, tracks whether the action was completed, verifies whether the underlying evidence changed, and compares subsequent AI observations when sufficiently comparable data exists. It reports an evidence-verified state and an observed outcome such as improved, unchanged, declined, insufficient, or unknown; evidence and re-observation can remain pending, unavailable, or not comparable. It does not claim that the intervention caused the AI change. Lifecycle: Recommended action → completion → evidence verification → comparable re-observation → observed outcome state.
For live AI visibility measurement, AuthoritySignal currently supports four configured AI provider integrations: OpenAI / ChatGPT (gpt-4o-mini), Perplexity (sonar), Anthropic / Claude (claude-haiku-4-5-20251001), and Google Gemini (gemini-2.5-flash). 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 Competitive Authority Comparison where qualifying observations and comparable evidence exist; Intervention Verification for supported competitive-authority actions: completion, evidence verification, comparable re-observation, and observed outcome states; Authority & Evidence Intelligence, Authority Graph relationships, Authority Hub workflows, and approved Public Authority Profiles; Recruiting intelligence, office reports, recruiting toolkit workflows, and office/regional visibility where configured; Campaign Center content activation for market, community, social, email, and citation-oriented content; Listing Visibility and Property Intelligence, including Property Strategy Reports and controlled listing observations for ready listings; Hosted property landing pages with consumer inquiry capture
CONTROLLED BETA / ENTERPRISE PILOT capabilities where deployed: Configured brokerage or regional websites and hubs; IDX/MLS/RETS-connected enterprise web experiences; Recruiting lead generation and routing, and broader consumer lead routing where deployed
LIVE / PROVEN — ENTERPRISE-MANAGED capabilities where configured: Authority Refresh / AI Discovery Refresh is available through the enterprise platform as a managed, status-disciplined workflow where configured. It coordinates supported publishing, structured-data, sitemap, cache or CDN, access checks, discovery notifications, and later crawler or provider re-observation steps where technically available, helping accelerate rediscovery after a meaningful authority update. AuthoritySignal does not control independent crawlers or AI systems, does not force a recrawl, guarantee a refresh or recommendation, or instantly update a model; customer-facing status reflects observable events or verified system actions.
ROADMAP: AI recruiting coach and conversion guidance with recommended next steps, scripts, follow-up timing, and engagement guidance are not represented as current platform capabilities until a supported implementation is available.; Broader self-serve Authority Refresh automation beyond configured enterprise workflows remains subject to product availability and supported integrations.
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.