Looks like you're in . Want the local site?
AI VISIBILITY AUDIT · AI可視性監査
Your organisation has invested significantly in digital presence — but AI engines are now answering the questions your buyers are asking, and your brand's representation across those systems has never been formally measured. The AI Visibility Audit is a 47-point diagnostic across 12 AI engines, delivered in 5 working days, with a prioritised action roadmap that gives your marketing, digital, and procurement teams a documented, scored baseline for AI brand visibility. Every finding is structured for internal reporting, executive review, and implementation hand-off.
We are proudly featured on
Trusted by businesses we have shipped growth for
/ This is for you if
Enterprise marketing and digital strategy teams at listed companies and large privately-held organisations whose procurement processes require vendor deliverables to be formally scoped, scored, and presentable to internal stakeholders. The audit is designed with this requirement in mind: every output is documented, scored, and structured for internal circulation.
Technology and software companies operating in Japan whose B2B buyers are increasingly using Japanese-language AI engines — including those built on LLMs fine-tuned for the Japanese market — as part of their vendor research process. If your brand is not represented accurately in Japanese-language AI responses, you are absent from an important and growing part of the buying journey.
Global brands with Japan market operations that need to understand whether their AI brand representation in Japanese differs materially from their English-language representation — and whether Japanese-language AI engines are citing them accurately or not at all.
Corporate communications and IR-adjacent teams at companies where brand accuracy in AI-generated content carries regulatory or reputational weight. The LLMO Accuracy Score component of the audit is particularly relevant where factual precision in AI-generated brand descriptions matters to compliance or investor relations.
/ What's broken
AI engines that are widely used by Japanese business buyers — including Japanese-language interfaces of global platforms and Japan-specific AI services — do not simply translate English-language answers. They draw from different source sets, knowledge graph structures, and training data. A brand with strong English-language AI visibility may have close to zero presence in Japanese-language equivalent queries.
Your company may be described differently in Japanese-language sources than in English — different founding dates, different product descriptions, different service categories. AI engines aggregate these inconsistencies, and the result is a brand representation that undermines confidence among Japanese business buyers who verify claims rigorously.
Most schema implementations are built for English-language crawlers and indexers. Japanese-language hreflang, structured data in Japanese character sets, and entity representations relevant to Japanese knowledge graphs are typically absent from even well-maintained technical SEO implementations.
Japanese enterprise procurement cycles require evidence-based decision-making. Without a formally scored AI visibility baseline, your organisation cannot demonstrate to internal stakeholders whether AI visibility investment is producing measurable outcomes.
/ What we engineer
Each workstream is built by the team that audits it, and wired into the rest of your growth system.
frequency of brand citation in AI-generated answers across both English and Japanese-language query sets
share of brand mentions in AI-generated responses relative to identified competitors, measured separately for Japanese and English language contexts
accuracy of AI-generated descriptions of your products, services, corporate structure, and positioning in both languages
consistency and completeness of your brand entity across Japanese and English knowledge graph sources
structured data implementation quality, with specific assessment of Japanese-language schema coverage
direct comparison against three competitors across the same query set in both languages
/ What changes
/ Common questions
Straight answers on scope, timelines and cost. Anything else, ask us directly.
Ask us directlyThe audit covers 47 distinct checks across six dimensions — AEO citation rate, GEO brand mention share, LLMO accuracy, entity completeness, schema quality, and competitive AI citation gap — tested across 12 AI engines using 50 or more queries in both English and Japanese. You receive scored results, a structured findings report formatted for internal distribution, and a 90-day action roadmap.
Five working days is the minimum required to conduct bilingual testing across 12 AI engines at the depth the audit demands. Running 50-plus queries in both English and Japanese, capturing and analysing responses, building the competitive comparison, and producing a structured, scored report that meets enterprise documentation standards cannot be compressed without sacrificing the quality of the findings.
Pricing is quoted in JPY and is based on audit scope, the number of languages included, and the complexity of the competitive set. Contact Ignited Nepal for a formal written quote. All pricing is provided before any engagement begins, with full scope documentation suitable for internal procurement approval.
The audit is a complete, standalone deliverable. Your internal teams can act on the 90-day action roadmap directly, or you may engage Ignited Nepal for implementation support. The report is structured to be handed off to any technical or content team without requiring additional explanation from us.
The standard audit covers 12 engines. For Japan-market clients, this includes Japanese-language interfaces of global platforms — ChatGPT, Perplexity, Google AI Overviews, Microsoft Copilot, Google Gemini, Claude, and Meta AI — alongside Japan-relevant AI services. The precise engine list is confirmed during onboarding based on your specific market and buyer behaviour.
The audit delivers both a scored diagnosis and a prioritised action plan. The 90-day roadmap is structured as an implementation brief: each finding is ranked by impact and effort and assigned to a responsible function. It is designed to move directly into execution without requiring a separate strategy engagement.
Start here
Your buyers are using AI engines as part of their research and vendor evaluation process. The AI Visibility Audit tells you exactly how your brand is represented across 12 AI engines — in both English and Japanese — what is suppressing your citation rate, and which changes will improve it fastest. You receive the full 47-point report, competitive gap analysis, and 90-day action roadmap within 5 working days, structured for enterprise reporting and implementation hand-off.
AIエンジンはすでにあなたの顧客の質問に回答しています。あなたのブランドが引用されているかどうかを確認してください。Ignited Nepal
Growth engineering · replies within 1 business day
By continuing you agree to our privacy policy.
