01
Define
Freeze the buyer-intent questions, category rules and configured engines.
Independent AI recommendation benchmarks
See where AI ranks your product.
Independent benchmarks of how major AI APIs recommend products. Every published edition records the model, question, date and reviewed evidence.
Observed results · Transparent evidence · Never paid rankings
Climb on evidence, not promotion.
RankHigh measures how AI engines actually recommend products — independently of advertising, sponsorships or founder activity.
- Standardised buyer-intent questions
- Configured AI engines
- Inspectable evidence
- Never paid rankings
Launch benchmark
AI Meeting Assistants
The first official AI Meeting Assistants benchmark is published. Explore the results, methodology and edition evidence.
Official edition published
The first official AI Meeting Assistants benchmark is live.
Explore the published rankings, the edition context behind each position and the methodology used for this edition.
From question to published result
Three stages. Full provenance.
02
Observe
Repeat the same questions and preserve model, timing and response provenance.
03
Review
Validate the evidence, score under the approved methodology, then publish a dated snapshot.
Evidence-first intelligence
We don’t just show a score. We show what produced it.
Every published result can carry the provider, exact model, tested surface, buyer-intent question, sample context, observed recommendation and methodology version.
Explore the evidence standardDated snapshots
No undated rank claims.
Commercial firewall
Payment never changes rank.
Reviewed evidence
Public metadata is deliberately curated.
Versioned methodology
Changes are labelled, not hidden.
The provider panel
Four perspectives. Equal weight.
The benchmark uses official web-enabled APIs from four provider families—not their consumer apps. Each contributes equally to the score.
Each family contributes 25%. Provider and API configurations are frozen for each edition. The edition page identifies available public metadata and disclosure limitations. No provider sponsorship or endorsement is implied.
AI visibility, with context
When AI becomes a shortlist, evidence matters.
A recommendation can introduce a buyer to a product—or leave it out. RankHigh documents those observations under consistent conditions. We measure recommendations; we do not control them.
For founders
Understand your observed visibility.
Inspect your product’s position in the published edition. Changes can be compared once additional comparable editions are published. Automated monitoring and alerts are not available yet.
Inspect published resultsFor buyers
Inspect the recommendation, not just the rank.
Compare published products in the same category and edition, then inspect the model, question, date and reviewed evidence behind each result.
Explore comparisonsProduct discovery
A product missing from the conversation?
Public nominations are coming soon. When they open, nomination will not guarantee inclusion, and nomination volume will never improve rank.
Questions, answered
Before you check your rank.
Independent by design
See where AI ranks your product.
Official AI Meeting Assistants results are published. Explore the rankings and the evidence standard today.