AI Reputation Stack · three packages
AI Reputation Stack: the network of sources AI reads about you
You may already have a Wikipedia page, but it is a single node. ChatGPT, Gemini, Claude and Perplexity cross-check facts across Wikipedia, Wikidata, the media, communities and other sources. AI Reputation Stack works on the whole network of sources so that it describes you correctly. Foundation €2,490, Authority €6,900, Enterprise Reputation OS €14,900.
// €2,490 / €6,900 / €14,900 per project · paid contribution disclosed in WikiBusines' name · the result is a probability, not a guarantee
01The shift
From a single Wikipedia page to a managed network of sources
A Wikipedia page is a strong first node. But AI engines never rely on a single page: they read the network of sources together. The product is no longer the article. It is the consistency of the whole network around it.
In one line: we have already built the page. The next step is to make the entire network of sources around it say the same accurate thing, to machines and people alike.
02Why it matters
A thin network of sources: a risk, not just a gap
You are not buying "more visibility". You are reducing the risk of looking wrong, fragmented or invisible at the moment a machine, or a buyer, checks.
One question, three versions
Two records instead of one
Q____1Company N is a football club
noneCompany N is a sensor manufacturer
The loudest source writes the answer
Checked before the call
The old figure comes back
Make the source graph consistent before a machine or a buyer checks it.
03The network of sources AI reads
Layers of the source network AI reads: one foundation, several signals
ChatGPT, Perplexity, Gemini and Google AI Overviews share a common base of high-trust sources. Each layer below adds a distinct signal and reinforces the previous one. We build them in sequence, from the cheapest and most fundamental, and we are honest about the weight of each.
The encyclopedic anchor
- Why AI relies on it
- In independent studies, Wikipedia is one of the most cited sources in ChatGPT and Perplexity answers, and part of the training data of large models. It is possible only where notability genuinely holds, so we assess that first.
A machine-readable entity (Q-id)
- Why AI relies on it
- The ID of the entity that AI services and knowledge graphs work with. Without it you are a string of letters; with it you are a known thing AI can reason about.
A licensed-image layer
- Why AI relies on it
- Correctly licensed logos and photos are used by search engines and image-recognition services, so the visual AI pulls up is the one you chose.
Trust by market
- Why AI relies on it
- An AI answering in German pulls German sources first. Entities in other languages extend precise coverage to the markets you need, wherever the page can genuinely be defended.
Density of independent sources
- Why AI relies on it
- Contextual citations inside topically relevant articles increase the density of independent links around your entity: reinforcement that both editors and AI weigh.
Discovery and AI retrieval surfaces
- Why AI relies on it
- AI reads community discussions when it forms answers. A useful, policy-safe footprint raises the chance of being represented in the discussions AI retrieves. We frame this as discovery and probability, never as a guaranteed mention.
Keeps the record consistent
- Why AI relies on it
- An open record drifts: third-party edits, outdated facts, disputes. Continuous monitoring and a source-correction plan keep the whole network on one accurate message over time.
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We do not sell "presence on eight wiki farms". Trust sits at the foundation; the other layers only reinforce it. Where your sources support a real Wikipedia page, it becomes the anchor: Wikipedia notability assessment →
04What we highlight
What AI will know about your brand: flagship products, differentiators, a balanced account of crises
The network of sources is a chance to show AI what you are genuinely strong at: flagship products and services, and the unique features that set you apart from competitors. At the same time, conflicts, crises and controversial incidents are presented neutrally and in balance: the facts, the decisions and your position alongside the criticism.
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We do not remove criticism from sources: that breaks the rules and does not work. We aim for the full picture, so that next to a loud headline stand the decisions, the consequences and your position.
05An honest difference
Reputation in AI answers: we shape the network of sources, we do not manipulate the machine
The market is full of services promising to "make" AI mention you or to "own the answer". Nobody can honestly do that. We do the opposite: we make the public sources these systems read accurate and complete, through disclosed, policy-compliant work.
What we do NOT do
- ×We do not force AI to mention you in every answer. Nobody can honestly do that.
- ×We do not make undisclosed or promotional edits. Paid contribution happens only with proper disclosure.
- ×We do not guarantee that a specific AI will say a specific thing. Providers control their own logic.
What we actually do
- ✓We document your entity in the high-trust sources AI already relies on.
- ✓We work neutrally and source-first, with talk-page management, monitoring and escalation.
- ✓We measure real AI citations over time (Authority and Enterprise), so you can see the probability rise.
On compliance: paid contribution to Wikimedia projects is allowed only with proper disclosure of the paid relationship. We disclose it in WikiBusines' name and work through neutral sourcing, COI-safe requests, talk-page management and monitoring, never through undisclosed promotional editing. Editing your own page directly is high-risk and often challenged; disclosed, source-first work is the durable route.
06Three packages
AI Reputation Stack packages: Foundation, Authority, Enterprise Reputation OS
The three packages are assembled from proven WikiBusines work, not from separate line items. Prices are per project, in EUR. Regular support keeps the network consistent after launch.
Foundation
Foundation is the floor. One market, a basic entity presence. The minimum that ends your exposure as a single node.
- English Wikipedia page where notability genuinely holds, after a notability and sourcing assessment (and a realistic alternative route if it does not)
- Wikidata entity with verified properties: a machine-readable record
- Wikimedia Commons: your logo plus one hero image, correctly licensed
- 90 days of monitoring after publication, then Managed Protection at €1,500/year
Result: a defensible anchor and a real entity in the knowledge graph: the basis for a Google Knowledge Panel and first AI citations.
Start with FoundationAuthority
Authority is the default. B2B, two or more markets, active growth. Our default recommendation, with the best value-to-coverage ratio in the stack.
- Everything in Foundation
- A Wikipedia page in a second language and consistent multilingual Wikidata
- 10 contextual Wikipedia links for a denser base of independent sources
- AI visibility audit and work on entity accuracy in the sources the models trust
- Baseline measurement of AI citations in ChatGPT, Claude and Perplexity
- Managed Protection and monitoring at €1,500/year
Result: your page becomes a network of sources in two markets, and AI citations are measured against a baseline. The record accumulates instead of drifting.
Start with AuthorityEnterprise Reputation OS
Enterprise Reputation OS is for high-stakes situations. Fundraising, M&A, regulated industries, contested or high-scrutiny brands: where reputation is a board-level matter.
- Everything in Authority, in three modules
- Authority Expansion: English plus two additional Wikipedia language versions, Wikidata in five languages, 20–30 contextual links
- Machine Knowledge Layer: a source-based knowledge hub, full LLM-citation measurement, monthly reporting
- Defense & Narrative Layer: Reddit and Quora, SLA-backed governance, a source-correction crisis plan, OSINT
- Program retainer from €2,300/month: governance, monitoring, reporting and protection
Result: a managed reputation operating system: a multilingual network of sources, an LLM knowledge layer, monthly reporting and a defense plan. A version you can show the board.
Start with Enterprise| What is included | Foundation | Authority | Enterprise OS |
|---|---|---|---|
| Notability and source assessmentBefore any work on the page, with a realistic alternative route | ✓ | ✓ | ✓ |
| English-language Wikipedia pageWhere notability genuinely holds | ✓ | ✓ | ✓ |
| Wikidata recordWith verified properties | ✓ | ✓ | 5 languages |
| Images on Wikimedia CommonsLogo and main image with correct licences | ✓ | ✓ | ✓ |
| 90 days of monitoring after publicationThen Managed Protection at €1,500 a year | ✓ | ✓ | ✓ |
| Second marketWikipedia page in a second language, consistent Wikidata | — | ✓ | +2 languages |
| Contextual links from Wikipedia | — | 10 | 20–30 |
| AI visibility audit and data accuracyAn audit of your visibility in AI and work on the accuracy of data about you | — | ✓ | ✓ |
| Measurement of AI citationsChatGPT, Claude and Perplexity, reports on a schedule agreed at the start | — | baseline | monthly |
| Reddit and Quora, SLA-backed governance, OSINT | — | — | ✓ |
All work is source-first and disclosed. Every result is phrased as a probability we can measure, not a guarantee. The terms are in our guarantees → Need a smaller scope? AI visibility packages €800–€3,500 →
07Enterprise Reputation OS
Enterprise Reputation OS: three modules
Any module can be launched on its own once Authority is in place.
08Google results
Negative results on the first page of Google: what can change and what cannot
Old-style ORM sold a single promise: make negative links disappear from the first page of Google. We do not sell that. Truthful coverage is not removed on request, by us or by anyone else. What moves the first page, and with it AI answers, is the strength of an accurate record around you. That is the work, in three parts.
- 1Company N: official websitecompany-n.com
- 2"Company N disrupted deliveries": aggregator blognews-aggregator.examplefalse claim
- 3Company N: Wikipediauk.wikipedia.orgstrengthened
- 4Interview with the founder: business publicationbusiness-daily.exampleindependent source
- 5Editorial correction: delivery datanews-aggregator.examplecorrected at the source
When the record first needs to be checked, we start with a confidential OSINT investigation →, and then annual support → keeps the anchor accurate.
09How we work
How we work on AI Reputation Stack: contact, reports, incidents
Foundation
- Contact
- A named project manager for the whole engagement and the 90-day monitoring window
- Reporting
- Stage updates during the work, then alert notes within Managed Protection
- Escalation
- Email, replies during business hours
Authority
- Contact
- A named project manager across both markets
- Reporting
- Measurement reports against the AI-citation baseline, at a frequency agreed at the start
- Escalation
- Priority handling within Managed Protection
Enterprise Reputation OS
- Contact
- A dedicated program manager: one person accountable for the whole program
- Reporting
- Monthly program report: LLM-citation measurement, network changes, work completed
- Escalation
- 24/7 escalation channel for active incidents; response times are fixed in the contract SLA
When the record needs support beyond the wiki layer, we coordinate adjacent channels: independent media through the media program →, executive profiles through LinkedIn management →; we coordinate advertising but do not run it. Available on any package as additional work; in Enterprise, as standing workstreams within the retainer.
10Start here · AI Reputation Snapshot
AI Reputation Snapshot: what AI says about you and where the gaps in your source network are
One page: what ChatGPT and Perplexity say about you right now, whether you have a Wikidata entity and a Knowledge Panel, where the language and source gaps are, and which package closes the biggest one. For a deeper baseline, the full AI visibility audit (from €490) is a separate deliverable and is not credited toward packages.
Request a snapshot11Why us
Why WikiBusines for reputation in AI: services we have delivered since 2010
12Frequently asked questions
AI Reputation Stack: frequently asked questions
How does AI Reputation Stack differ from the AI visibility packages?
The AI visibility packages (€800–€3,500) build the source layer and measure AI answers before and after. AI Reputation Stack starts with a Wikipedia page and builds a network of sources in one or more markets, with oversight after launch.
Can negative results be removed from the first page of Google?
Nobody removes truthful coverage. We strengthen accurate sources, correct false coverage at the source through publishers and talk pages, and measure the shift in a before-and-after report.
Why does Wikipedia matter for ChatGPT and AI search?
Large language models and AI answer engines give heavy weight to authoritative encyclopedic sources. Brands that exist on Wikipedia and Wikidata are cited consistently and accurately; those that do not are paraphrased loosely or skipped.
How does AI visibility differ from SEO?
SEO optimizes a page you control. AI visibility builds the base of sources AI systems read about you: Wikipedia, Wikidata, Reddit threads, Quora answers, structured media. It is editorial, source-first work, not technical work.
Do you guarantee that my brand will appear in ChatGPT answers?
No. Model providers control their own retrieval and training. We can build source infrastructure that materially raises the probability, and we monitor how the major AI systems describe your brand over time.
Can I get a Google Knowledge Panel without a Wikipedia page?
Sometimes. A well-structured Wikidata entity, plus steady independent coverage, plus clean schema markup on your own properties may be enough for a panel to appear for a sufficiently well-known entity. But Wikipedia remains the strongest single signal, and panels built without it are thinner and less stable. If a Wikipedia page is not on the table right now, we start with Wikidata and work on the source base, and tell you honestly what coverage that will give.
How much does a Wikipedia page cost?
English company page from €2,400 (individual €1,620). Tier-1 other languages: €1,800/€1,400. 40 Tier-2 languages (UK/FR/ES/PT/JA/KO and others): €1,500/€1,250. All other languages (Tier-3): €900/€700. The full table is on the pricing page.
Are there discounts for multilingual portfolios?
Yes. A multilingual launch shares the research and the source pack, which multiplies the savings. The agency discount depends on the number of pages in the order: 2–3 pages, 4%; 4–5, 10%; 6–7, 15%; 8–10, 20%; 11+, 22%.
Which payment methods do you accept?
SWIFT, SEPA, Wise, Payoneer, PayPal, Visa and Mastercard credit cards, USDT (TRC-20).
Why does English Wikipedia cost more than other languages?
English is the flagship version: the highest visibility, the strictest source scrutiny, the largest community of patrollers, the strongest influence on Google and AI systems. Volunteer review of an English draft is materially heavier than in most other languages, which means more research, more cited sources and more reviewer time on our side. The price reflects that volume of work, not a markup.
Do you guarantee the page will be published?
No, and nobody honestly can. Wikipedia is an independent community with its own editorial review. What we do guarantee is a risk-managed process. We do not propose publication until the source base can support it. 93% of the pages we create pass Wikipedia's review and are published.
What happens if the page is deleted after publication?
Throughout the 90-day monitoring window we defend the page and republish if needed. If it cannot be restored after 3 attempts in that window, we refund 80% of the project amount.
Do you guarantee a Google Knowledge Panel?
No. Knowledge Panels are produced by Google's own systems, which draw in part on Wikidata and Wikipedia. Our work materially raises the probability that a panel appears, but the final decision rests with Google.
Do you disclose that you are paid to edit Wikipedia?
Yes, on every project, every time. The Wikimedia Terms of Use require paid contributors to disclose the contracting company, the client and the ultimate beneficiary. We disclose this on the editor's user page, on the article talk page at creation, and in edit summaries during the work. This is non-negotiable. We decline projects that ask us to hide the relationship: undisclosed paid editing is the number one reason such work gets banned and pages get deleted.
Related pages
Order an AI Reputation Snapshot for your brand
Send us a brand brief. We will show what AI says about you today and which package closes the biggest gap.
- 1Brand and websiteName, website, the markets where you operate.
- 2What already existsA Wikipedia page, a Wikidata record, key publications.
- 3What concerns youFalse facts in AI, negative results in search, entering a new market.
or write to us: team@wikibusines.com · Telegram