Content
Does your site contain short answers, definitions, FAQ, HowTo, and product descriptions that AI models can understand and cite?
RiseChat.ai Docs
AI Visibility documentation for brands that want to be cited by AI.
A practical guide to making your brand easier to understand in AI Overviews, AI search engines, ChatGPT, Perplexity, Gemini, Claude, Grok, and other model answers. Use it as a map from content audit and Schema JSON-LD to llms.txt, deployment, and citation monitoring.
Quick map
Four layers of AI visibility.
Schema
Are the most important facts described with Schema JSON-LD in the head section, and can models connect the brand, product, and offer?
Context
Do llms.txt and llms-full.txt help AI systems read priority content without guessing?
Monitoring
Do you know how ChatGPT, Gemini, Perplexity, and other systems describe your brand and competitors?
Definitions
Concepts to understand before a GEO/AEO audit.
AI Visibility
Brand visibility in AI answers
The work that makes a brand easier to understand, cite, and recommend in AI Overviews, AI search engines, ChatGPT, Perplexity, Gemini, Claude, Grok, and other model answers. It covers content audit, Schema, page optimization, and citation monitoring.
Example
A brand recommended by ChatGPT when asked for the best HEPA air purifier up to 45 m².
GEO
Generative Engine Optimization
Optimization for generative AI: brand, category, features, and advantages described clearly so a model can cite or recommend the brand.
Example
A SaaS site describes its use cases, alternatives, limits, and FAQ so AI can compare it with competitors.
AEO
Answer Engine Optimization
Content shaped as short, direct answers to user questions. Answer engines can retrieve a specific fragment instead of interpreting long marketing copy.
Example
An FAQ section answers in a single paragraph: how is Schema different from SEO?
SEO
Search Engine Optimization
Optimization for classic web search results: indexation, keywords, linking, and technical SEO. It is still the foundation, but it is not enough when AI gives users a ready answer.
Example
An article ranking in web search's top 10 for a phrase, then a user clicks through.
Schema JSON-LD
Structured data for search engines and AI
A JSON-LD fragment that describes a page, product, company, FAQ, HowTo, or application so machines can read meaning without guessing from layout.
Example
A product page uses Product schema, an FAQ uses FAQPage schema, deployed through a snippet in the head.
llms.txt
Context file for language models
A text file with important resources, descriptions, and site context for AI systems. llms-full.txt provides a deeper version for richer analysis.
Example
The file includes the product description, links to documentation, pricing, FAQ, and use cases.
Direct answer
A short answer ready to be cited
A compact block of content that answers one question without preamble. It is easier to summarize and reuse in an AI answer.
Example
RiseChat.ai generates Schema, analyzes content, and monitors how AI talks about the brand.
AI brand perception
How models describe the brand
The associations, category, advantages, and limits that a model attributes to a brand. Monitoring detects whether AI understands the brand the way the company intends.
Example
The model describes the product as an SEO tool, even though the company positions it as an AI Visibility platform.
Comparison
SEO, GEO and AEO work together, but measure different decision moments.
Goal
- SEO
- Rank in web search results.
- GEO
- Appear in AI answers.
- AEO
- Provide a short answer to a user question.
Format
- SEO
- Articles, landing pages, and keyword-focused pages.
- GEO
- Structures, sources, definitions, brand context.
- AEO
- FAQ, HowTo, definitions, and direct answers.
Discovery
- SEO
- User clicks a web search result.
- GEO
- AI cites or recommends the brand.
- AEO
- The engine pulls out a ready fragment.
Risk
- SEO
- Traffic loss from zero-click results.
- GEO
- Missing Schema limits citability.
- AEO
- Generic content is not citation-ready.
Features
What RiseChat.ai does after providing a domain.
Feature 1
Content audit
First layer: we check whether content is understandable to AI models and ready to be cited.
- Detect missing FAQ, HowTo, definitions, and direct answers.
- Find pages that describe products too generically.
- Prioritize changes that improve citation readiness.
Feature 2
Schema JSON-LD
We turn visible content into machine-readable data for the site head section.
- Generate 10 Schema types: Organization, WebSite, WebPage, SoftwareApplication, FAQPage, HowTo, BreadcrumbList, Article, BlogPosting, Service.
- Schema matched to the real page content, not detached declarations.
- Deploy through a snippet in the head section, on your own or with an agency.
Feature 3
llms.txt and llms-full.txt
Context files that help AI systems read priority content without guessing.
- Summarize the offer, category, features, FAQ, and sources.
- Short variant llms.txt plus the deeper llms-full.txt.
- Keep structure aligned with product and content changes.
Feature 4
AI visibility monitoring
Ongoing control over how models describe the company, product, and category.
- Check whether the brand appears in answers to key questions.
- Detect incorrect descriptions and missing advantages.
- Compare visibility against competitors on the same prompts.
Feature 5
Content change suggestions
Concrete recommendations that turn generic marketing into citable answers.
- Proposals for new sections, headings, and direct-answer blocks.
- Shift language from declarations to operational product descriptions.
- Guidance on where to add sources, examples, and comparisons.
Work process
From site crawl to AI answer monitoring.
- 1
Site audit
We check how AI reads your site today: content, structure, internal linking, and FAQ.
- 2
Change list
You get a plan for what to add, rewrite, or remove across pages, FAQ, and product cards.
- 3
Schema JSON-LD
We generate 10 Schema types and deliver a snippet for the head section.
- 4
Page optimization
We rewrite the pages where AI loses context: products, features, offers, and services.
- 5
Monitoring
We check how AI describes your brand and flag fixes when model responses change.
Stack
The stack we put on every site we work with.
Each layer below goes through the same loop: built from your real pages, tested against the AI models it targets, and shipped only when model answers confirm it works. Nothing leaves our hands on a guess.
- Schema JSON-LD01Stack
Schema JSON-LD
We generate structured data (Schema JSON-LD) and deliver a ready code snippet for the head section of your site. The same Schema helps classic web search, AI Overviews, and AI models such as ChatGPT, Gemini, Perplexity, Claude, and Grok at the same time.
- We rewrite content for citability02Stack
We rewrite content for citability
Headlines, descriptions, FAQ, service pages, categories, product pages, and comparisons become short, concrete answers. AI reaches for them because they're ready to drop into a response.
- We give models context about your company03Stack
We give models context about your company
We generate llms.txt and llms-full.txt that summarize your offering. Models don't have to guess what you do, what you sell, or who you serve.
- We break your content into AI-friendly blocks04Stack
We break your content into AI-friendly blocks
We change what you already publish into FAQ, HowTo, ItemList and other readable sections, then build optimizations on top of the content that already lives on your site.
- We monitor what AI says about your brand05Stack
We monitor what AI says about your brand
Every 48 hours we ask the models on your plan, from ChatGPT and Gemini to Perplexity, Claude, Grok, and DeepSeek, about the company and its competitors. External models refresh their knowledge at different speeds, so we monitor changes over at least two weeks and keep iterating until answers stabilize.
Implementation
Minimal plan for preparing a site for AI search.
This checklist keeps visible content, structured data and context files in one axis. This is important because the AI model compares information consistency from multiple sources.
- 1Enter the domain and type: store, SaaS, agency, or B2B service.
- 2Get a change list: missing FAQ, HowTo, definitions, page descriptions, and sections that are hard to cite.
- 3We deploy Schema JSON-LD in the head, on your own or with an agency.
- 4Rewrite key pages around customer questions and add FAQ.
- 5Monitor AI answers regularly, because models change faster than rankings.
Questions
Short answers for teams starting GEO/AEO.
Does Docs replace the landing page?
No. The landing page sells the value, Docs organizes concepts and the implementation process.
Does AI Visibility replace SEO?
No. It extends SEO with AI-answer visibility. Indexation and technical SEO are still the foundation.
Where should I start with optimization?
Start with a content audit, then add definitions and FAQ, Schema, key page improvements, and monitoring.
Next step