Make AI recommend your brand
ReasonGo covers the whole chain, from AI visibility monitoring and site GEO audits to the content pipeline and delivery sign-off, so your brand earns citations and trust in the AI search era.
- Daily sampling across major AI engines
- Pinpoints why your brand is not cited
- Content drawn from real brand sources
- Citation changes diffed automatically after release
01/AI visibility monitoring
See how AI engines actually cite your brand
ReasonGo tracks how your brand shows up in DeepSeek, Doubao, Qwen, ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews, and measures visibility, share of voice and citation sources, so every AI answer becomes a chance to be seen.
Multi-engine coverage
Monitors the major AI search platforms in one pass, so no mention slips through.
Prompt management
Define the questions your business depends on and keep them as a sampling baseline.
Citation detection
Tells you whether your domain is cited and where in the answer it appears.
Share of voice
Quantifies your standing against competitors inside AI answers.
Opportunity list
Suggests what to write next, based on the questions you do not cover.
Trend reports
Charts month-over-month movement so you can see what the work did.
Covered engines
Share of voice in AI answers
02/Site GEO audit
Find the root cause behind missing citations
ReasonGo audits the site across technical SEO, structured data, content structure and AI crawler access, pinpoints what is blocking citations, and turns the findings into work orders you can execute.
Six-dimension site score
Technical SEO, structured data, content structure, AI accessibility, performance, internationalization.
AI crawler simulation
Replays how GPTBot, ClaudeBot and the rest crawl the page, and checks the HTML they actually receive.
Schema coverage check
Verifies which structured data types, such as FAQPage and Product, are in place.
llms.txt check
Confirms the file exists and is well formed, so key sources are declared.
Gap report
Lists where you lead competitors and where you fall behind.
Work order generation
Turns each finding into a work order with acceptance criteria attached.
Six-dimension site score
61- GPTBot / ClaudeBot can access
- FAQPage and Product schema deployed
- llms.txt missing, key sources undeclared
03/Brand content pipeline
Produce content AI wants to cite, at scale
ReasonGo builds the whole pipeline from knowledge base to multilingual delivery. RAG-style semantic chunking plus AI generation keep a steady supply of answer-first, fact-dense content, and a quality gate checks accuracy and compliance before anything ships.
Industry knowledge base
Stores products, certifications, commercial terms and terminology in a structured form.
Semantic chunking
Splits knowledge so AI engines can retrieve and cite it more easily.
AI content generation
Drafts answer-first product pages, FAQs and technical articles from the knowledge base.
Multilingual translation
AI translation backed by a glossary and human review, so localization holds up.
Quality gate
AI checks plus human review filter out factual errors and compliance risk.
Automatic schema injection
Every piece of content ships with its own JSON-LD structured data.
Multi-site delivery
Publish to your own sites in one click, across Astro, Next.js, WordPress and more.
- 1
Industry knowledge base
Products · certifications · rules · terminology
- 2
Semantic chunking
Splits knowledge for retrieval and citation
- 3
AI content generation
Answer-first pages / FAQs / articles
- 4
Quality gate
AI checks + human review
- 5
Multi-site delivery
Astro · Next.js · WordPress
04/Implementation and sign-off
A closed loop from diagnosis to verified impact
ReasonGo turns findings into work orders, deploys schema, llms.txt and improved content automatically, then re-samples the AI answers to verify the result. Monitor, diagnose, implement, verify: one loop, closed.
Work orders
Each one carries the problem, the fix, the acceptance criteria and an owner.
Automatic schema deployment
JSON-LD is generated and injected straight from the work order.
llms.txt generation
Built and deployed automatically from plugin registry data.
Automatic publishing
Approved content is pushed to the target sites on its own.
Automatic verification
Re-samples AI citations after the work lands and diffs before against after.
Work order write-back
Passing verification closes the ticket, which removes most manual sign-off.
Per-prompt comparison
Shows the citation change for each prompt, so the impact reads at a glance.
Monthly review report
Wraps up what shipped and how visibility moved, and feeds the next round.
Monitor
Re-samples AI citations
Diagnose
Pinpoints the cause
Implement
Deploys schema, llms.txt, content
Verify
Per-prompt diff and write-back