AI Visibility Infrastructurefor modern discovery
Define a machine-readable source of truth for your business so AI systems can understand you more clearly and represent you more consistently.
Gemmetric helps businesses publish and validate identity, measure AI interpretation over time, and turn signal gaps across GEO, GEM, AI Perception, and AI Identity into deployable fixes.
Built for businesses that need evidence they can stand behind.
Private beta: we review requests and invite businesses as capacity opens.
Fast facts
Clear definitions you can cite
AI Visibility Score
Gemmetric's blended top-line score across GEO, GEM, AI Perception, and AI Identity.
It reflects the combined state of structural readiness, external corroboration, model interpretation, and canonical identity.
GEO
On-site readiness across structure, schema, metadata, and intent coverage.
GEM
Off-site corroboration across trusted sources, listings, profiles, and other external signals.
AI Perception
How AI systems currently define and understand the business, including current confidence and interpretation quality.
AI Identity
The canonical identity loop: define, publish, validate, and observe the business in machine-readable form.
AI is already deciding who gets seen
Search engines return lists. AI assistants return answers.
AI Visibility is driven by four things: how readable your site is, how well the public web corroborates it, how models currently interpret it, and whether you have published a clear canonical identity they can reference.
GEO — Generative Entity Optimization
On-site readiness: structure, metadata, schema, and intent coverage.
GEM — Generative Entity Model
Off-site corroboration: the strength, consistency, freshness, and coverage of external signals that support the entity.
AI Perception
How models currently define and understand the business, including current confidence and interpretation quality.
AI Identity
Canonical identity infrastructure: define, publish, validate, and observe a machine-readable business identity.
AI Visibility Score
Gemmetric's blended top-line score across GEO, GEM, AI Perception, and AI Identity.
It reflects the combined state of structural readiness, external corroboration, model interpretation, and canonical identity.
The four pillars behind the roll-up
If those layers are weak, recommendation confidence drops. You usually do not see that in analytics, because the user never clicks through. Scores are computed from what we can observe, and blocked access is called out explicitly.
- Can the site be parsed cleanly (structure, schema, metadata)?
- Do public signals consistently corroborate what the business claims?
- How do models currently define and understand the business?
- Has the business published a clear canonical identity AI can retrieve and verify?
Traditional SEO optimizes for
Being found
- Keywords, backlinks, metadata
- Clicks, impressions, and rankings
- Retrieval: which page should show up?
AI visibility optimizes for
Being chosen
- Clarity, corroboration, perception, and identity reliability
- Answerability for real user intents
- Confidence: can the model recommend this?
This is why “more content” does not automatically help. If your schema is incomplete, your business identity is inconsistent across listings, or your pages are hard to parse, the model hesitates.
What you get after a scan
Clear fixes you can apply
On supported plans, you get pillar scores for GEO, GEM, AI Perception, and AI Identity, plus the blended AI Visibility Score and Fix Packs with deployable schema and copy. Engineers can ship JSON-LD, marketers can update content blocks, and everyone can see the delta after the next scan.
See the workflow →GEO
On-site readiness
GEM
Off-site corroboration
Consistency • Freshness • Coverage
AI Perception
Current model understanding
Awareness, trust, and interpretation quality
AI Identity
Canonical identity loop
Ledger • Gateway • Validation • Observation
AI Visibility
Roll-up across four pillars
GEO Score
Schema + metadata opportunity
GEM Score
Corroboration gaps detected
AI Perception
Interpretation confidence is mixed
AI Identity
Gateway + validation incomplete
AI Visibility Score
Blended view across all four pillars
Top Fix Pack (example)
Add LocalBusiness + Service schema, clarify primary category language, and publish an FAQ block aligned to customer intent.
Deployable output
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Your Business",
"url": "https://example.com",
"sameAs": ["https://..."]
}Fix Packs
Go from audit to deploy without the hand waving
Traditional tools stop at diagnostics. Fix Packs bundle the evidence, the recommended change, and deployable outputs. That can mean GEO fixes, GEM corroboration work, AI Identity publishing steps, and copy updates shaped by what AI Perception is showing now.
See what you get →What’s wrong (evidence)
- Missing Service + FAQ schema on key pages
- Inconsistent primary category language
- Thin intent coverage for “comparison” queries
The fix (deployable)
- GEO fixes: JSON-LD + metadata + intent-aligned copy
- GEM fixes: strengthen corroboration across profiles, listings, and trusted references
- AI Identity fixes: publish and validate a clearer canonical identity
- Priority ordering shaped by current AI Perception blockers
Export bundle
JSON-LD snippet, copy blocks, CSV diagnostics, and a PDF-ready summary. Everything you need to implement.
Trust & accountability
Enterprise posture built in
The difference between a cool AI tool and a system a business can rely on is operational truth. You need traceability, repeatability, and transparency.
Sample metrics shown for illustration.
Success rate (rolling)
99.2%
See reliability over time. No black boxes.
Avg scan duration
42s
Latency spikes can indicate site or routing issues.
Failure rate by domain
0.8%
Surface blocked crawlers, robots rules, and auth walls.
SLA compliance
On target
Enterprise posture: measurable, auditable delivery.
You get the same operational transparency we use internally.
Read the SLA story →Avoids
- Rank tracking dashboards
- Keyword volume charts
- Content-at-scale generators
- Black-box automation
Focuses on
- Machine-readable clarity (structure + schema)
- External corroboration across trusted sources
- AI perception diagnostics and AI identity validation
- Deployable Fix Packs with measurable deltas
FAQ
Common questions
What is AI Visibility?
AI Visibility Score is Gemmetric's blended top-line score across GEO, GEM, AI Perception, and AI Identity. It reflects the combined state of structural readiness, external corroboration, model interpretation, and canonical identity.
What is AI Visibility Infrastructure?
AI Visibility Infrastructure is the system a business uses to define, publish, validate, and observe how AI systems understand it over time. In Gemmetric, that means making identity more explicit, consistent, and directly referenceable instead of leaving AI systems to infer it from scattered signals alone.
What does Gemmetric produce after a scan?
Gemmetric turns scan findings into outputs businesses can use, including prioritized findings, deployable schema and copy recommendations, Fix Packs, exports on supported plans, and re-scan validation over time.
If AI visibility matters to your business, this is the infrastructure built for it.
We’ll review your request and invite you when a slot opens. No hype. No shortcuts. Just clarity you can defend with data.