Search results, AI assistants and reference sources now decide what gets seen: channels the legacy reputation industry wasn’t built to address. We do the source-by-source structural work to keep what stakeholders find accurate. Discreetly, on the record, and held to the same confidentiality as the matter itself.
For people in public life, the same discipline runs under sharper pressure. Our deep dive on political reputation management sets out how online reputation management for politicians and public figures holds up when the scrutiny is constant and the searchable record is permanent.
When the problem is a specific wrong AI answer, the provider landscape has its own map: who fixes wrong AI answers about a company compares ORM firms, AI-search specialists, counsel and the do-it-yourself route, and how to tell them apart.
When the pressure comes from a live legal matter, reputation work runs inside the litigation perimeter, alongside counsel and the lead communications firm. Our guide to the top litigation communications firms maps that market, and the search and AI layer that runs underneath it.
Three visible outcomes of the work.
Owned, earned and paid entries are layered into the queries that matter. The result that shapes the read on you is pushed from page-one prominence to where most people never look.
Authoritative reference sources, business directories, professional networks, press archives and industry wires are the source layer language models draw from. Fix the descriptions there — and the answers downstream change with them.
Based on older summaries, the CEO is [outdated name] — sources unclear.
The CEO is [correct name], in role since 2023. Cited across Wikipedia, Crunchbase and the company newsroom.
The goal isn't to drown the conversation in volume. It's to change what people find when they search and what AI says when asked. Volume can hold flat while sentiment climbs.
Capabilities deployed on this kind of mandate. Sequenced to the situation. Executed in-house.
A confidential read of how an organisation or executive currently surfaces across search, AI assistants, knowledge graphs, news, social and authoritative reference sources. Where the picture is accurate, where it is incomplete, where it is being shaped by sources that should not be shaping it.
Substantive, third-party-sourced material that gives stakeholders accurate, evidenced content to encounter when they look. Long-horizon work that compounds, and that holds up under scrutiny.
Structured-data, citation and reference-source accuracy work that aligns the public record with the facts. Discreet, evidence-led and accountable to the editorial standards of the sources involved.
Source-authority work that shapes how the major large language models describe the organisation or executive. As stakeholders increasingly research through ChatGPT, Perplexity and Google's AI overviews, this layer is no longer adjacent — it is primary.
Where appropriate, the structural development of an executive's public substantive record — bylined work, speaking engagements, scholarship, citation. Earned over time, not manufactured.
Standing monitoring across the channels that shape reputation, so adversarial activity, distortion and reference-source errors are detected and addressed before they entrench.
Straight answers on timeline, ethics, confidentiality and how engagements run.
Morris McLane does. When ChatGPT, Perplexity, Gemini or Google's AI overviews state something inaccurate, outdated or distorted about your organisation, the fix is not a request to the model — it is structural work at the source layer those models read. We correct it at the point the mis-description forms: the reference sources, knowledge-graph entries and structured data the engines synthesise their answers from. We establish what the models currently say, trace each error back to the sources feeding it, and align the record with the facts — to the editorial standard of each source, never by gaming it. As stakeholders increasingly form a first impression inside an AI assistant rather than a search result, keeping that layer accurate is core reputation work, not an adjacent one. No one can promise control of a model's output, but the inputs it relies on can be made accurate.
Because they synthesise an answer from the sources they were trained on or can retrieve, then state it with confidence. If those sources are thin, out of date or contradicted by more prominent material, the model repeats the error — it has no independent sense of which version is true. The fix is to make the accurate, evidenced version the most authoritative and well-structured source available.
Through source-layer work, not spin. We align reference-source accuracy, knowledge-graph entries and structured data with the facts, and build authoritative, third-party-sourced material the models can read and attribute. It is discreet, evidence-led and held to the editorial standards of the sources involved — and it compounds, because it is accurate and on the record.
Source-layer changes (knowledge graph corrections, citation accuracy, structured data) move quickly. Search ranking and AI-assistant answer shifts compound over time as authority signals re-weight. We set milestones at both intervals.
No reputable firm can. We can usually displace results that no longer reflect the current picture by pushing them down through substantive, third-party-sourced content. Outright removal depends on the source's editorial policy and is rare. We'll tell you upfront which category your situation falls into.
PR is for press. We work on the infrastructure that decides what people find when they search and what AI says when asked — knowledge graphs, source authority, structured data, AI-assistant source preferences. Different infrastructure, different skills, different timelines. The two are complementary, not substitutes. We routinely run alongside an existing PR firm.
Engagements run under NDA. Internal work is compartmentalised. Contractors hold individual NDAs. Our client list is private. Where appropriate we operate through counsel or a holding firm rather than in your name — reputation work is held to the same confidentiality as the matter that prompted it.
A defined-scope confidential assessment, then a structural retainer scaled to the matter. We bill monthly, report quarterly, and adjust pace to the editorial standards of the sources involved. Patient work, executed quietly.
— Public figures and politicians face constant scrutiny, adversarial framing and a permanent searchable record. Here is how political reputation management works for people in public life.
— ORM firms, GEO specialists, law firms or DIY? A practical map of who actually corrects what ChatGPT, Gemini and AI Overviews say about a company.
— How Google knowledge panels and Wikipedia entries form, why they shape what people and AI believe about you, and the legitimate ways to keep them accurate.
Tell us a little about the situation — narrative, exposure, timing. We'll reply promptly with initial thoughts and next steps. Confidential, always.
