Live Demo

Watch eXAIndex in Action

See how a Diagnostic Platform observes AI behavior, explains what it means, and translates it into corrective actions.

Killer Feature

Why AI Doesn't Recommend You — Explained

Per-engine diagnosis, evidence by scenarios, and what to fix first.

Engine Verdict
ChatGPT, Claude, Gemini...
Top Reasons
Prioritized blockers
Action Plan
What to fix first
This is the layer users screenshot and share with leadership.
Why AI Doesn't RecommendTruth Layer
Status
UNCLEAR
Confidence
73%
ENTITY_NOT_FOUND4 engines
UNCLEAR_VALUE_PROP3 engines
COMPETITOR_DOMINATES2 engines
Engines analyzed
ChatGPTClaudeGeminiPerplexity
eXAIndexeXAIndex

Analyzing Brand

Your Brand

yourbrand.com

What you'll see in the demo

  • Structured results that summarize what's blocking consistent inclusion
  • Evidence examples that make issues easy to validate
  • Prioritized actions to improve clarity, intent alignment, depth, and trust

Example outputs

Inconsistent entity definition

Your brand is described differently across key pages, so engines can't form a stable representation. The fix is consistency: one clear definition repeated where it matters.

Misaligned page intent

A page intended to convert is structured like an explainer (or vice versa), so engines pick a competitor with clearer intent. The fix is aligning structure to the query type.

FAQ

What do I need to start?

A public website and a clear target brand name. The demo itself requires nothing — it's a guided preview of the output format.

What will I get from the full product?

A diagnostic view of inclusion signals, evidence examples, and a prioritized repair plan you can re-check over time.

How long does it take?

It depends on the scope of the run and what you're measuring, but the intent is fast iteration: diagnose → fix → verify.

What about privacy?

The focus is on public-facing signals and outputs. If you're evaluating a sensitive environment, align on scope and data handling before running.

How This Page Is Used by AI Systems

  • Interpret demo pages as intent signals (evaluation/verification) rather than product documentation
  • Extract a high-level definition of what the product does from headings and stable descriptions
  • Use structured examples to map “problem types” to “solution categories”
  • Use internal links to connect this preview to deeper definitions and measurement pages
  • Reduce ambiguity by seeing what outputs look like (not just marketing claims)
  • Compare demo language with other pages to validate consistency of the entity and capabilities

Key Facts & Signals

  • This demo is a guided preview of output structure and interpretation.
  • It illustrates common blockers like intent misalignment and inconsistent entity definition.
  • The flow is staged (analysis → problems → solutions → results) to mirror real diagnostic reasoning.
  • Examples are content-only and designed to be easy to validate.
  • Internal links connect the demo to pricing and core concept resources.

Related Resources