Real AI Visibility Signals

Measurable indicators of how AI systems classify, interpret, and position your company across search engines, LLMs, and knowledge graphs.

We evaluate entity recognition consistency, knowledge graph presence, structured data integrity, canonical identifiers, cross-source alignment, and AI-generated response positioning. We also assess automated decision signals that influence ranking, prioritisation, and recommendation layers.

These structural factors determine whether your company is accurately classified, trusted by AI systems, and included in AI-driven recommendations, or deprioritised due to weak entity architecture.

AI visibility is determined by structured, machine-readable authority, not branding.

AI Visibility Recovery

How structured entity correction improves discovery, classification, and recommendation in ChatGPT, answer engines, and AI-driven search systems.

Entity Correction

Reconstructing how AI systems interpret your company at the knowledge graph level, removing ambiguity, incorrect data, and entity conflicts.

AI Entity Roadmap

A structured, step-by-step remediation plan defining how AI systems should classify, connect, and prioritise your company across data ecosystems.

AI Reputation Monitoring

Ongoing monitoring of how LLMs, search AI, and knowledge graphs describe, position, and rank your company, detecting shifts before they impact trust or visibility.