AI app for marketing · no coding needed
AI answer visibility and citation workbench
Replace several rented AI-visibility tools with one owned workspace that tracks brand presence across AI models, measures share of voice against competitors, and turns findings into reviewed actions.
Made for: Brand and communications teams tracking how their brand appears in AI-generated answers
What it does for you
The problem
Brands cannot see where AI models mention them, which sources are cited, or what to fix, so visibility work is guesswork.
What it gives you
Reviewed AI visibility report with prioritized actions
What you give it
Permitted prompt setsmodel outputscited sourcesbrand facts
Build your own version of Citable, Justblank and more
One app with what these 5 AI tools do, yours to keep and change: Citable, Justblank, LLM SEO Report, Insights by Omnia, AdMesh.
Everything these tools do, in one app
- AI answer visibility tracking Shows where and how a brand appears inside AI-generated answers.Found in Citable, Justblank, LLM SEO Report and 1 more
- Multi-model coverage Tracks brand presence across multiple AI models such as ChatGPT, Gemini, and Perplexity.Found in Citable, Justblank, LLM SEO Report
- Citation tracking Captures which sources are cited in AI answers and how often.Found in Citable, Insights by Omnia
- Share-of-voice measurement Measures the brand's share of mentions compared to competitors in AI answers.Found in Citable
- Competitor mention tracking Shows which competitors are mentioned or recommended for specific AI prompts.Found in Justblank, Insights by Omnia
- Prompt visibility and volume Identifies which queries matter for discovery and tracks their visibility and volume.Found in Justblank
- Prioritized action recommendations Provides specific, prioritized next steps to improve AI visibility.Found in Citable, Insights by Omnia
- Content generation Generates ready-to-use content such as social posts and blog posts.Found in Citable, Justblank
- Content optimization Optimizes content to be more likely to appear in AI answers.Found in Justblank
- Community discovery Finds relevant online communities and posting opportunities.Found in Citable
- Content scheduling Schedules content to be published at optimal times.Found in Citable
- Campaign tracking Tracks the performance of content campaigns over time.Found in Citable
- Brand recognition analysis Analyzes how well AI models recognize and know a brand.Found in LLM SEO Report
- Brand URL and social account identification Identifies official brand URLs, third-party websites, and social media accounts recognized by AI models.Found in LLM SEO Report
- Recommendation strength insights Shows how strongly an AI model recommends a brand, distinguishing popularity from endorsement.Found in LLM SEO Report
- Outdated information detection Detects outdated or incorrect brand information present in AI training data.Found in LLM SEO Report
- Search context comparison Compares how search context influences AI recommendations when combined with other SEO reports.Found in LLM SEO Report
- Citation gap analysis Shows external sources that cite competitors but not your brand.Found in Insights by Omnia
- Action tagging and handoff Tags actions by type to help hand off tasks across teams.Found in Insights by Omnia
- Daily citation collection Collects citation data daily to keep insights current.Found in Insights by Omnia
- Market-specific insights Generates insights per country for different markets.Found in Insights by Omnia
- Shareable insights and exports Allows insights to be shared and exported for team use.Found in Insights by Omnia
- In-chat recommendations Places product recommendations natively inside AI chat responses when user intent is detected.Found in AdMesh
- Performance-based billing Charges based on actions such as clicks, signups, or purchases.Found in AdMesh
- GEO analysis Reviews website content to improve organic visibility in AI-generated responses.Found in AdMesh
- Platform and brand controls Provides controls like frequency caps, allowlists/blocklists, category targeting, geo and pacing.Found in AdMesh
- Transparency and reporting Explains why an item was shown and tracks click-to-conversion.Found in AdMesh
How it works, step by step
- Track where and how the brand appears inside AI-generated answers
- Cover multiple AI models such as ChatGPT, Gemini and Perplexity
- Capture which sources are cited in AI answers and how often
- Measure the brand's share of mentions against competitors
- Show which competitors are mentioned or recommended for specific prompts
- Identify which queries matter for discovery and track their visibility and volume
- Provide specific, prioritized next steps to improve AI visibility
- Generate ready-to-use content such as social posts and blog posts
- Optimize content to be more likely to appear in AI answers
- Find relevant online communities and posting opportunities
- Schedule content to be published at optimal times
- Track the performance of content campaigns over time
- Analyze how well AI models recognize and know the brand
- Identify official brand URLs, third-party websites and social accounts recognized by AI models
- Show how strongly a model recommends the brand, separating popularity from endorsement
- Detect outdated or incorrect brand information present in AI training data
- Compare how search context influences AI recommendations
- Show external sources that cite competitors but not the brand
- Tag actions by type to hand off tasks across teams
- Collect citation data daily to keep insights current
- Generate insights per country for different markets
- Share and export insights for team use
- Place product recommendations inside AI chat responses when user intent is detected
- Charge based on actions such as clicks, signups or purchases
- Review website content to improve organic visibility in AI-generated responses
- Apply controls such as frequency caps, allowlists, blocklists, category targeting, geo and pacing
- Explain why an item was shown and track click-to-conversion
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed AI visibility report with prioritized actions with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for AI answer visibility and citation workbench with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds AI answer visibility and citation workbench with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare26 KB
- prompt-vps.mdThe same build on your own server (Docker)26 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria10 KB
- demo/index.htmlThe working demo on sample data198 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Replace several rented AI-visibility tools with one owned workspace that tracks brand presence across AI models, measures share of voice against competitors, and turns findings into reviewed actions. For brand and communications teams tracking how their brand appears in AI-generated answers, convert permitted prompt sets, model outputs, cited sources and brand facts into a reviewed AI visibility report with prioritized actions. The benefit is a testable hypothesis, measured through tracked prompts with current visibility data and accepted actions per reporting cycle; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect permitted prompt sets, model outputs, cited sources and brand facts, then follow this sequence: 1. Track where and how the brand appears inside AI-generated answers. 2. Cover multiple AI models such as ChatGPT, Gemini and Perplexity. 3. Capture which sources are cited in AI answers and how often. 4. Measure the brand's share of mentions against competitors. 5. Show which competitors are mentioned or recommended for specific prompts. 6. Identify which queries matter for discovery and track their visibility and volume. 7. Provide specific, prioritized next steps to improve AI visibility. Resolve uncertain cases with qualified reviewers, approve reviewed AI visibility report with prioritized actions, and measure tracked prompts with current visibility data and accepted actions per reporting cycle against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Prompt sets and model access are limited to permitted sources; final brand claims and publication decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve brand voice, source attribution, quotation accuracy and usage permissions. Brand owners approve substantive claims and publication scope. One brand, one market and a bounded prompt set; final brand claims and publication decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One brand, one market and a bounded prompt set; final brand claims and publication decisions remain human. Implement one approved input format, a bounded representative case set and the first three task modules: track where and how the brand appears inside AI-generated answers; cover multiple AI models such as ChatGPT, Gemini and Perplexity; capture which sources are cited in AI answers and how often. Support the remaining modules with operator review: measure share of mentions, show competitor mentions, identify priority queries, provide prioritized next steps, generate and optimize content, find communities, schedule content, track campaigns, analyze brand recognition, identify brand URLs and social accounts, show recommendation strength, detect outdated information, compare search context, show citation gaps, tag actions, collect daily citations, generate market insights, share and export insights, place in-chat recommendations, charge per action, review website content, apply controls, explain why an item was shown, compare against baseline, capture corrections and export the reviewed report. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Brand-owned websites, permitted analytics and authorized social accounts. Cloud storage, content management and reporting destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Prompt and brand setup, Visibility dashboard, Citation and source explorer, Action queue, Client report and export. Use a project list for brands and markets, a central dashboard for visibility and share-of-voice trends, and a right-hand panel for cited sources, competitor mentions and review comments. Let users compare models and time periods side by side. Display draft, changes requested and approved states. Provide a shareable report link with comments anchored to the relevant finding. Make the task-specific outcome reviewed AI visibility report with prioritized actions visible beside its evidence, review state and value baseline.
