Visibility
Check whether AI systems mention the brand clearly or bury it behind competitors and generic alternatives.
AI Perception Checker
Check how AI systems currently frame an agency website. Review the Brand Perception Index preview, then decide whether competitor and source gaps deserve the complete 5-credit Presence, Perception, Preference, and AI Readiness workflow.
Check how AI describes your brand
Enter a brand name. VectorGap returns a quick perception score so you can see whether AI answers create a visibility, accuracy, or recommendation risk.
Check your brand's AI recommendation gap in 30 seconds. We ask multiple AI models about your brand using standard discovery prompts, then aggregate the scoring across the models that return successfully.5-credit audit
No credit cardFast AI signal3 free checks/month
Accuracy
Spot whether AI answers repeat outdated, vague, or wrong facts before those answers reach prospects.
Sentiment
See whether the model frames the brand as trusted, risky, niche, unknown, or irrelevant.
Use the checker as an initial signal, not the final diagnosis
Run a quick brand-name perception check without waiting for a full dashboard setup.
Review the BPI preview and unlock the breakdown for visibility, accuracy, sentiment, and recommendation risk.
Escalate weak or ambiguous signals into the 5-credit audit for prompts, competitors, sources, and first fixes.
Use the full VectorGap intelligence loop when clients need recurring Perception, Presence, and GEO proof.
From free perception signal to white-label proof
The checker is an initial signal. Use it to decide when a brand needs the 5-credit audit, remediation sprint, same-target retest, and white-label report.
| Buyer question | What the free checker can expose | Agency next step |
|---|---|---|
| Is the perception signal strong enough to act on? | The free perception signal can expose whether AI describes the brand clearly, buries it behind competitors, repeats outdated facts, or frames it as risky for a buyer prompt. | Use the 5-credit audit when the signal needs provider evidence, competitor context, source analysis, and market, language, persona targeting before client work starts. |
| What should the agency fix first? | A weak score can point to missing entity facts, weak citation sources, unclear category positioning, thin proof pages, or recommendation-risk language. | Scope a remediation sprint around answer blocks, source repair, proof pages, entity facts, schema/FAQ cleanup, and competitor comparison gaps. |
| How does the client see progress? | The initial check defines the before-state: current framing, weak source layer, competitor pressure, and the likely reason the brand is not recommended confidently. | Run a same-target retest after fixes and export a client-ready report that compares perception, source quality, competitor pressure, and recommendation framing. |
A weak AI perception score usually has a source-layer cause
The checker gives you the fast signal. The deeper work is finding whether AI systems are missing the right public facts, quoting weak sources, confusing competitors, or failing to see enough proof to recommend the brand.
Missing entity facts
Company, product, pricing, audience, and proof facts are not clear enough on stable public pages.
Weak citation layer
AI systems have too few consistent sources to justify mentioning or recommending the brand.
Competitor dominance
Competitors appear more often because their public truth layer is easier to retrieve and compare.
Recommendation risk
The brand may be visible but not framed as the safest or most relevant choice for buying prompts.
AI perception questions
What is AI perception?
AI perception is how assistants and answer engines describe, evaluate, compare, and recommend a brand when users ask discovery, category, and buying-intent prompts.
Is this the same as a full LLM audit?
No. This free checker gives an initial signal. The full VectorGap audit tests more prompts, competitors, providers, source evidence, history, and remediation priority.
What should I do if the score is weak?
Use the 5-credit audit to validate whether the issue is missing public facts, weak citation sources, inaccurate model memory, competitor dominance, or poor recommendation framing.
Can a brand rank in Google and still fail here?
Yes. Search rankings and AI recommendations are related but not identical. AI systems may ignore well-ranked pages if the source layer is unclear, inconsistent, or not easy to cite.
What to fix after the check
- Add concise answer blocks to product, category, pricing, and proof pages.
- Consolidate brand facts into one stable public truth layer.
- Align external profiles, partner pages, directories, and social descriptions.
- Compare prompts where competitors are recommended and your brand is absent.
Escalate into the full intelligence loop
This utility catches one early Perception signal. The 5-credit audit connects that signal to prompts, competitors, web sources, GEO evidence, and white-label remediation.