We assess first
Most executives are not notable by Wikipedia's standards, and no amount of spend changes that. We will tell you before you spend anything. Roughly two-thirds of enquiries end here, and that is a good outcome.
Practice area 06
Wikipedia & knowledge panel
The structured-entity layer: what Google shows in the box beside your name, and what every AI assistant repeats when someone asks who you are. Handled within the rules, because the alternative is worse than having nothing.
Why this matters more than it did
Machines answer first now.
A growing share of searches about a person never produce a click. The searcher reads a panel or an AI summary and moves on. Those surfaces are built from structured, independently sourced data — which means the question is no longer only what ranks, but what the machines believe.
What we work on
- Notability assessment — an honest read on whether an article is even possible
- Independent-source development, because sourcing is the whole game
- Policy-compliant disclosure and talk-page engagement, never covert editing
- Factual correction requests on existing articles, properly declared
- Knowledge panel claiming, verification and correction
- Entity consistency across Wikidata, Crunchbase, registries and your own structured data
- Monitoring for adversarial edits and coordinated vandalism
Honest position
What we will and will not do
We declare conflicts
Paid contribution without disclosure breaches the terms of use, and when it is discovered the article is deleted and the discovery itself becomes a search result. We use declared requests and talk pages only.
We build sourcing
The route to an article is independent coverage in reliable publications, which is why this practice runs alongside earned media rather than instead of it. Sourcing first, article later.
We fix the panel
Knowledge panels can be claimed, verified and corrected directly, and can often be improved even where no Wikipedia article exists. This is frequently the faster win.
We hold the entity
Panels and AI answers pull from many structured sources. Getting them to agree with each other is unglamorous and it is most of the actual work.
We monitor
Articles get vandalised, particularly during disputes and funding events. Monitoring catches it before it is mirrored across a hundred scraper sites.
Common questions
Straight answers
Can you guarantee a Wikipedia page?
No. Notability is decided by volunteer editors against published criteria, and paid guarantees are a red flag. What we can do is assess honestly whether you meet the bar, build the independent sourcing that would support it, and make a properly declared request.
My knowledge panel has wrong information. Can that be fixed?
Usually, yes, and often within weeks. Panels can be claimed by the subject and correction requests submitted. Where the error comes from an upstream source, we fix the source — otherwise the correction reverts at the next refresh.
Someone keeps editing my article with false claims.
That is handled through Wikipedia's own dispute processes, with declared conflict of interest, not by reverting from an undisclosed account. Persistent bad-faith editing can be escalated to administrators, and for defamatory material there are legal routes as well.
Does any of this affect what ChatGPT says about me?
Directly. Assistants lean heavily on Wikipedia, Wikidata and high-authority coverage. If those sources are thin, wrong or absent, the model fills the gap — sometimes plausibly and incorrectly. Fixing the sources is the only durable fix.
The structured layer
This box is read more often than your website.
A knowledge panel is assembled from structured, independently sourced data. It can be claimed and corrected by the subject — which most executives never do, so the errors simply sit there.
Private enquiry
Start with an honest notability read.
It is a short piece of work and it will often save you a great deal of money.