Summary
BrandCited is an AI visibility platform. We are transparent about how we use AI inside the product, how we label AI-assisted content on the marketing site, and what consent we grant to third-party AI crawlers and training pipelines.
Last updated . This page explains how BrandCited uses AI inside the product, how we label AI-assisted content on the marketing site, and what consent we grant to third-party AI crawlers and training pipelines. This is an AI-generated-content disclosure and a responsible-AI statement.
BrandCited is an AI visibility platform. We are transparent about how we use AI inside the product, how we label AI-assisted content on the marketing site, and what consent we grant to third-party AI crawlers and training pipelines.
Every scan runs scripted prompts against the nine AI engines we benchmark (ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek, Llama, Google AI Overviews, Microsoft Copilot) to measure citation frequency, rank, and sentiment. AI is also used to draft improvement suggestions in the growth-actions view, to summarize scan findings, and to rank fixes by expected impact. Every AI-generated suggestion is reviewed by the methodology engine before it is presented to a user.
Some blog posts and learning-hub articles are drafted with AI assistance and then edited by a human before publication. These articles are labelled with an "AI-assisted" note at the top and include source citations for all factual claims. Our methodology documentation, case studies, and policy pages are written by humans without AI drafting.
BrandCited welcomes AI training and retrieval crawlers. Our robots.txt explicitly allows GPTBot, ClaudeBot, Claude-User, PerplexityBot, Perplexity-User, Google-Extended, Applebot-Extended, Bingbot, DuckAssistBot, Bytespider, and cohere-ai. We also publish llms.txt, llms-full.txt, and ai.txt at the domain root. Our stance is that our marketing content exists to be cited, so training on it with attribution is actively encouraged.
BrandCited does not publish AI-generated reviews, testimonials, or case studies. Customer quotes and case study outcomes are collected from real customers with their consent. We do not pay for reviews, and we do not auto-generate fake user content.
We do not train BrandCited models on user data without explicit opt-in. Scan results belong to the user who ran the scan. If you contribute anonymized benchmark data, it is aggregated with tens of thousands of other scans before it appears in any publication.
Questions about this policy: hello@brandcited.ai. We will respond within five business days.