Hedgehogeo.Ai gives growth teams a single operating layer fordiscovering the questions that shape AI answers, measuring brand presence across leading AI engines, and turning evidence into executable content work — with every decision traceable back to a real answer.
ONE WORKSPACE / FOUR SIGNALS
Hedgehogeo.Ai is built around evidence, not vanity dashboards. Each workspace links the AI answer, the prompt behind it, competitive context, and the next action your team can own.
Track mentions, position, citation sources and brand sentiment at the answer level across the AI engines your audience uses.
Compare the same question across brands to expose missing proof, weak positioning and opportunities where your category is still open.
Build a living question library from research, search signals and AI response patterns. Rank every question by value, intent and brand opportunity.
Route gaps into content briefs, source placements and review workflows, then measure whether the next monitoring cycle moved the answer.
Quantify mention rate, citation sources and sentiment for the real questions in your industry across leading AI engines.
Generate AI-friendly content (FAQ, comparisons, reviews) from key questions and your brand assets.
Distribute content to sources that AI engines actually cite, and watch visibility evolve on a continuous monitoring cycle.
We continuously publish articles about GEO, AI visibility, structured content, citation signals, and compliance so the homepage carries not only positioning, but also citable fresh content.
If a model cannot locate the answer, judge trust, and extract a quotable passage within seconds, the page is unlikely to become a stable source.
FAQ is one of the most model-friendly page formats, but only when the questions are real and the answers are directly quotable.
When the same company is described differently across its own website, social bios, and external mentions, it becomes harder for AI to unify those sources into one entity.
We are not just shipping a marketing interface. We are building Hedgehogeo.Ai as a platform that can keep evolving in production. The team includes members from institutions such as NUDT, RWTH Aachen, and HKUST, along with senior operators and architects from major internet companies including Tencent.
Core team members across algorithms, engineering, operations, and delivery
Patents, software copyrights, and trademark assets accumulated
Industry delivery tracks continuously refined
Major domestic and global AI platforms continuously monitored
The founder has received a national academic technology-progress award, and the team keeps turning frontier AI capability into deployable products through engineering discipline.
Our shadow model and content-review model work as a dual foundation, balancing AI-visibility monitoring accuracy with strict data and content-compliance boundaries.
We invest in durable assets across Q&A corpora, vertical templates, platform monitoring, and citation-source rules instead of relying on short-term traffic tricks.
We continuously track retrieval and citation behavior across leading generative search engines — from ChatGPT, Claude and Gemini to Wenxin, Doubao, Qwen and Kimi — so your brand answer stays consistently visible across platforms.
Start from an industry question graph, combined with search terms, social discussions and sales signals to surface the highest-value prompts for your brand.
Auto-generate FAQ, comparison, review and case study formats from your questions and brand assets — aligned with how LLMs retrieve and quote.
Industry directories, knowledge communities, content alliances, official knowledge bases — hit the citation sources LLMs really crawl, not generic traffic sites.
Daily monitoring of mention rate, citation sources and sentiment across multiple AI engines — feeding insight back into question mining and content strategy.
