Product
A platform for getting surfaced in AI answers.
Gemmetric measures GEO (on-site readiness) and GEM (model strength) and rolls them into AI Visibility—then turns the gaps into fixes you can deploy.
Think structure + schema, model strength (awareness, understanding, trust, and reach), AI Perception risk, and deltas you can track over time.
Private beta: we review requests and invite teams as capacity opens.
Core signals
AI Visibility is a roll-up of GEO + GEM
GEO measures on-site readiness. GEM measures model strength. Together, they determine how likely you are to be surfaced in AI answers.
GEO
Generative Entity Optimization
On-site readiness: structure, metadata, schema, and intent coverage.
GEM
Generative Entity Model
Model strength: awareness, understanding, trust, and reach.
AI Visibility
Roll-up score
Overall likelihood to be surfaced in AI answers—computed as a roll-up of GEO + GEM.
What you get after a scan
Clear fixes you can apply
You get core signal scores (GEO, GEM, and AI Visibility), diagnostics like AI Perception, and Fix Packs with deployable schema and copy. This is designed to plug into a real workflow. 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
Model strength
Awareness • Understanding • Trust • Reach
AI Visibility
Roll-up of GEO + GEM
GEO Score
Schema + metadata opportunity
GEM Score
Trust + reach gaps detected
AI Visibility Score
Roll-up of GEO + GEM
AI Perception
Misidentification risk detected
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 usually means GEO fixes (JSON-LD, metadata, intent coverage) and GEM fixes (actions that improve model strength by improving the inputs that influence it—especially trust and reach—plus copy written for real intent queries.
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: inputs that influence model strength (especially trust + reach)
- Priority ordering + estimated impact delta
Export bundle
JSON-LD snippet, copy blocks, CSV diagnostics, and a PDF-ready summary. Everything you need to implement.
Exports
Outputs teams can ship.
You should not need to translate a report into tasks. Outputs map directly to GEO and GEM fixes so teams can ship improvements without extra interpretation.