Generative Engine Optimization — get cited in AI search
Full-lifecycle GEO delivery: visibility audit → knowledge engineering → structured publishing → continuous monitoring
Who is yunyeyuanzhi
yunyeyuanzhi (云业元知) is a service provider focused on GEO, or Generative Engine Optimization. We believe AI-search visibility is not built by piling up content, but by real knowledge, clear structure, and continuous verification.
Core deliverables
- AI search visibility baseline report
- High-intent query matrix and competitor gap analysis
- Enterprise knowledge map and AI-citable content groups
- Schema structured publishing and internal linking network
- Monthly brand citation monitoring and iteration recommendations
GEO is not more content, but better reasons for AI to cite you
yunyeyuanzhi does not manufacture concepts or invent stories for companies. We diagnose query intent, brand entity, knowledge structure, and citation signals, then turn real business facts into knowledge assets that answer engines can understand, verify, and cite.
AI search visibility audit
Identify where the brand is absent in Doubao, DeepSeek, Yuanbao, and other answer engines, and separate entity gaps, content gaps, and attribution gaps.
High-intent query judgment
Separate brand, category, selection, and comparison queries to find the questions that actually shape buyer preference instead of chasing generic keywords.
Brand entity engineering
Help AI understand who you are, what you do, who you serve, and why you are credible, reducing omission, misattribution, and competitor confusion.
Citable knowledge structure
Turn business facts into excerpt-ready FAQs, case summaries, selection judgments, and service explanations that AI can quote consistently.
Citation monitoring and iteration
Retest core queries over time, track whether the brand is mentioned, cited, or recommended, and adjust content priorities as competitors move.
Sales conversation support
Turn AI-search customer questions into sales-ready judgment materials, moving conversations from basic explanation to differentiation.
GEO content engineering partner
Rebuilding AI semantic sovereignty in the zero-click decision chain—cross-industry visibility audits, knowledge engineering, and multi-engine citation monitoring
From AI absence to citation
AI semantic sovereignty · B2B selection
Rebuilding AI semantic sovereignty in B2B selection
24 decision queries · 8-week retest · citation 0% → 38%
The issue was not poorly organized existing materials. Public information was almost empty: the enterprise had no website and, aside from a few Douyin short videos, no AI-retrievable information assets. When procurement engineers asked AI, answers could only cite competitors' selection standards. Across 24 decision queries, the project built brand entity and selection authority from zero; after eight weeks, citation rose from 0% to 38%.
Methodology outputs：Diagnostic judgment · selection authority · citation monitoring
Read full case studyRAG retrievability · visual knowledge engineering
Transforming visual assets into answer-engine retrievable knowledge
18 decision queries · visibility 0% → 39%
The client was not absent online, but its signals were fragmented and hard to attribute: the website existed but lacked professional maintenance, had many 404s, and weak structure; content on Toutiao, Zhihu, and Baijiahao did not form one stable brand entity. The project reorganized visual assets, platform content, and project facts into citable knowledge. Across 18 decision queries, visibility rose from 0% to 39%.
Methodology outputs：Visual asset diagnosis · project knowledge · citation monitoring
Read full case studyAI school-choice visibility · brand trust governance
Diagnosing a visibility gap in AI-assisted school choice
8 AI platforms · 160 simulated queries · about 20% average mention
The group had genuine differentiators, including a digitally enabled campus model, but campus information was fragmented, authoritative outcome data was limited, and public complaints risked being amplified by answer engines. The audit covered eight mainstream AI platforms and 160 simulated queries. Average brand mention was about 20%, leading to a three-stage roadmap for risk response, content infrastructure, and trust building.
Methodology outputs：Visibility baseline · risk review · three-stage roadmap
Read full case studyGEO Solution
Not a one-off content update, but an accountable delivery path from diagnosis to retesting.
Visibility audit
Build a brand citation baseline around core business queries and identify competitor placement, content gaps, and entity attribution issues.
Knowledge engineering
Turn product, service, case, FAQ, and credential facts into AI-readable and excerpt-ready knowledge structures.
Structured publishing
Use pages, Schema, internal links, and content groups to answer high-intent questions that answer engines can retrieve and cite.
Monitoring iteration
Retest core queries monthly, track mentions, citations, and recommendations, then adjust priorities based on movement.
Frequently Asked Questions
What you need to know about GEO
What is GEO (Generative Engine Optimization)?→
GEO is a content optimization strategy for AI search engines and answer engines. Its goal is to earn brand citations when AI answers user questions—across Doubao, DeepSeek, Yuanbao, and major domestic AI search—not just fight for traditional search rankings.
When does an enterprise need GEO?→
When your target customers use AI to search for products, solutions, or industry knowledge, and AI answers frequently cite competitors instead of your brand, you need GEO. This is common in SaaS, manufacturing, professional services, consumer brands, and similar contexts—GEO applies whenever AI answers affect brand visibility.
Can a company do GEO without a website?→
Yes, but the starting point is not optimizing existing pages. The first step is creating a public brand entity and basic knowledge assets that AI can recognize. Even if a company has no website and only a few short-video appearances, it can begin with core business descriptions, credentials, product or service boundaries, customer-question FAQs, and case summaries, then build AI-citable content groups over time. The priority is helping AI understand who you are, what you do, and which scenarios you fit before measuring citation lift.
How do you measure GEO results?→
Key metrics include brand citation frequency for core keywords across major AI search platforms, competitor citation comparison, visibility changes on priority topics, and whether your content is retrieved and excerpted by AI. Our delivery includes continuous monitoring and iteration with verifiable data.
Have a specific need? Let's talk
Need better AI search visibility? We deliver practical GEO solutions.
Scan to add us on WeChat
Discuss your needs and next steps directly
Strategic partners
Partnering with outstanding teams to create lasting value
