Four defensive layers.
LLM Auditing
We continuously probe ChatGPT, Claude, Gemini, Perplexity and regional models — logging every inaccuracy, negative framing, and missing fact.
Hallucination Correction
Counter-content, citations, and direct model feedback to overwrite false narratives before they harden into training data and persist for years.
Deepfake Defence
Detection infrastructure, content watermarking, and rapid takedown playbooks — because synthetic attacks on your brand are accelerating.
Crisis Protocols
Pre-built response frameworks for AI-driven reputation crises: who acts, in what order, through which channels, within what time window.
Ongoing Monitoring
Always-on brand radar across LLM outputs, synthetic media channels, and dark-web signals — because threats don't run on business hours.
How we defend you.
01 · Audit
Probe every major LLM for current brand representation. Score accuracy, sentiment, and completeness across all models.
02 · Correct
Produce authoritative counter-content and submit corrections to model providers where possible. Seed the right narrative.
03 · Defend
Deploy watermarking, detection scripts, and takedown infrastructure to intercept synthetic attacks at source.
04 · Monitor
Continuous automated scanning with monthly reports and an incident escalation protocol that fires within 4 hours of detection.
Results clients typically see
98%
Hallucination detection rate
Our multi-model audit protocol catches 98% of factual inaccuracies, false attributions, and negative framings across 5+ major LLMs.
72h
Correction cycle
Average time from hallucination detection to authoritative counter-content published and submitted to model providers.
5+
Models monitored monthly
ChatGPT, Claude, Gemini, Perplexity, Grok — plus regional models relevant to your market — probed continuously.
<4h
Incident response SLA
Confirmed synthetic attacks, viral deepfakes, and high-severity hallucinations trigger a response within four hours.
The Theory
Reference guide by Brand Design Ltd., Varna, Bulgaria.
What is AI brand protection?
AI brand protection is the discipline of monitoring, correcting, and defending how your brand is represented inside Large Language Models and synthetic media. Unlike traditional reputation management — which focuses on human-readable search results and news — AI brand protection addresses the automated layer: what ChatGPT, Gemini, Claude, and Perplexity say about you when a human asks.
How do LLMs spread brand misinformation?
LLMs are trained on large corpora of web content and cannot distinguish reliably between authoritative sources and low-quality ones. They generate plausible-sounding text from statistical patterns — which means they can and do produce false attributions, invented lawsuits, incorrect founding dates, and inaccurate product descriptions. Once a model is trained on false data, that data persists until the model is retrained — which can take months or years.
What is a brand hallucination?
A brand hallucination is a factual error about your company or product generated by an AI model. Common types: incorrect founding date or history, fabricated legal or financial events, wrong product specifications or pricing, misattributed quotes or statements from executives. The danger is that hallucinations are presented with the same confidence as accurate facts — users rarely distinguish.
How does deepfake defence work?
Deepfake defence combines three layers: detection (automated scanning of social, video, and audio platforms for synthetic content using your brand assets or executive faces), watermarking (embedding invisible signals in all original brand content so fakes can be proven illegitimate), and takedown playbooks (pre-negotiated escalation paths with platforms for rapid removal).
What does Brand Design Ltd. deliver in a protection engagement?
A brand protection engagement delivers: an initial LLM audit across all major models with a full inaccuracy report, a correction programme (counter-content, citations, model submissions), a deepfake monitoring and takedown infrastructure, a crisis response playbook, and a monthly monitoring dashboard with incident escalation. The engagement runs continuously — not as a one-time audit.