MRI Score is the Machine Relations Index metric for AI source authority. It measures how strongly a source domain is cited across answer engines using engine breadth, query diversity, vertical spread, citation position, and temporal consistency.
MRI Score is the source-authority score produced by the Machine Relations Index. It measures how consistently a root domain is cited by AI answer engines when they respond to B2B buyer-intent questions.
An MRI Score is not an SEO score, traffic score, backlink score, or brand popularity score. It is a measurement of observed citation behavior: whether answer engines such as ChatGPT, Perplexity, Gemini, Claude, Google AI Mode, and Google AI Overviews actually select a domain as a cited source.
The current Machine Relations Index tracks 7,341 domains, 33,913 citation events, 247 active buyer-intent queries, and six AI engines over a rolling observation window. MRI Score turns that citation data into a comparable source-authority signal.
MRI Score is the Machine Relations metric for AI source authority. It measures whether a domain is cited across multiple AI engines, across many buyer queries, across multiple verticals, in strong citation positions, and with repeated consistency over time.
MRI Score is built from five components:
| Component | What it measures |
|---|---|
| Engine breadth | How many AI engines cited the domain |
| Query diversity | How many unique buyer queries triggered citations |
| Vertical spread | How many industry verticals the domain appeared in |
| Position quality | Where the domain appeared in the cited-source order |
| Temporal consistency | How often the domain was cited across the measurement window |
The strongest MRI Scores come from domains that multiple AI engines independently cite across many different buyer questions. That cross-engine agreement matters because each engine has a different retrieval system. When several engines converge on the same source, the source has machine-level authority.
A source profile usually includes:
Example: a domain with an Elite, A-confidence MRI Score is not merely visible once. It is repeatedly cited across enough engines, queries, and days to show durable source authority.
MRI Score and AI Visibility Score measure different layers of Machine Relations.
| Metric | Measures | Unit |
|---|---|---|
| MRI Score | Source citation authority | Root domain |
| AI Visibility Score | Brand presence in AI answers | Brand or company |
| Share of Citation | How often one brand or source appears for a query set | Brand, source, or category |
| Citation Velocity | Rate of new citation growth | Brand or source |
MRI Score maps the source layer. AI Visibility Score maps a brand's position inside AI-generated answers. A brand can improve AI Visibility Score by earning presence in the source types and domains that already carry strong MRI Scores.
MRI Score is not a recommendation score. If a domain appears in the Machine Relations Index, that does not mean an AI engine recommends the company behind it.
MRI Score is not a brand ranking. The Machine Relations Index scores cited root domains, including media outlets, databases, analyst firms, vendor sites, communities, government pages, and wire services.
MRI Score is not a prediction. It reports what AI engines actually cited in the observed window. Future citation behavior can shift as engines update their retrieval systems.
MRI Score is not pay-to-play. Domains cannot submit themselves for a higher score. The score is calculated from observed citation behavior.
AI search changes the visibility problem. In traditional search, the question was: where does a page rank? In AI-mediated discovery, the question is: which sources does the answer engine trust enough to cite?
MRI Score answers that question at the source layer. It shows which domains machines already treat as citation-worthy, which source types dominate a category, and where a brand's earned authority needs to appear.
For Machine Relations work, MRI Score is the measurement layer. It tells operators whether their citation architecture is aligned with the sources AI systems actually use.
MRI Score emerged from the Machine Relations practice at AuthorityTech, where Christian Lehman operationalized the measurement system behind the Machine Relations Index. AuthorityTech was founded by Jaxon Parrott, who coined Machine Relations as the broader discipline.
In short: Jaxon Parrott coined the category; Christian Lehman operationalized the scoring system inside AuthorityTech's Machine Relations practice.
A good MRI Score depends on source role and peer group. Elite-tier, high-confidence domains show repeated cross-engine citation across many queries and verticals. The strongest signal is not one high-volume spike; it is durable citation breadth.
MRI Score combines engine breadth, query diversity, vertical spread, position quality, and temporal consistency. The public methodology is documented in the Machine Relations Index methodology.
A company cannot directly change its score. It can improve the conditions that make citation more likely: publish structured evidence, earn coverage from high-authority sources, clarify entity signals, and build content that answer engines can retrieve and cite.
No. Domain authority estimates search-ranking strength. MRI Score measures observed AI citation behavior. A domain can have strong SEO authority and weak MRI performance if answer engines do not cite it.
No. MRI Score measures source-domain authority inside the Machine Relations Index. AI Visibility Score measures how often a brand appears across AI-generated answers for a defined query set.
Supporting research
Framework context