Operations for AI visibility

20 years in search. Now — the same thing, but for models.

The team has worked with organic traffic since the early 2000s. When ChatGPT, Gemini, and Perplexity appeared, we did not start a new company — the task is the same, the mechanisms changed. We have our audit engine for AI visibility, AI markup for owned surfaces, and a network of 100,000+ real people for research. Plus the old toolkit: PR, content, technical fixes, vendor coordination across multiple language markets.

20 years in searchOur audit engineNetwork of 100,000+ real peopleCoordination across multiple markets
How we work
01
Context and audit
We interview the team, run the site through the engine, and look at what AI systems say about the brand and category.
02
Work plan
We set priorities. We identify what we do ourselves, what goes to vendors, and what requires research with real people.
03
Foundation work
Fixes on owned surfaces, AI markup, entity alignment for the brand across the site, directories, and knowledge graphs.
04
Coordination
Parallel partner work: PR, content, localization, review infrastructure. One calendar, one point of responsibility.
05
Validation and reporting
Repeat run through the engine. What moved, what did not, which hypotheses held up or fell apart.

When visibility breaks, architecture is usually what breaks.

A team enters a new language market, calculates the traffic plan, then notices a month later: requests from ChatGPT and Gemini are three times lower than forecast. They check the technical layer — it is clean. They check the copy — fine. After two weeks of review, it turns out that in the new language their category is phrased differently, and under that phrasing the brand simply has no public history. Three competitor articles in August — and ChatGPT is already answering with their names.

These situations rarely happen for one reason. More often, several layers break at once — and while the team fixes the most visible one, the others pull down the result.

The category is phrased differently in this market

The team describes itself the way it is used to at home. Local users and AI systems talk about this category in different words — the brand does not enter the field.

The site is readable by people, but not by machines

The design is clear, the copy is alive. Machine markup is thin, the brand entity is fragmented, and ChatGPT assembles the picture from four independent scraps.

There are too few external traces

There are not enough independent mentions, citations, or relevant directories for AI systems to confirm the brand's claims. The brand itself sounds loud, but there is no echo outside.

More than the language diverges between markets

In one market, the brand reads as a solutions provider for large enterprises; in another, as a niche tool for developers. No one stitches the picture between markets, and each model assembles it itself, in its own way.

Vendors work in parallel, not together

The PR team writes in one voice, the developer is on the other side, the content writer runs a third line. Everyone is responsible for their piece. No one is responsible for how those pieces add up into one brand for the AI system.

Architecture ages faster than it seems

Six months ago, the category was phrased this way. Today, models have pulled in new sources, and the brand has quietly slipped down half a step. Without regular rechecks, this becomes visible a quarter later, when traffic has already been lost.

From a point report to full operational support.

You can come for a specific piece of work — you do not have to take everything at once. You can hand over visibility as a whole and focus on your own business — we hold the directions together as one team.

A
AI visibility audit
Our own engine runs the site in 20 minutes. Then a live specialist spends a couple of hours clarifying and preparing the report. You can see where the brand is read cleanly, where models lose it, and which step will create the fastest shift.
B
AI markup for owned surfaces
Structured data, entity alignment on the site and in external graphs, rewriting sections for model readability without losing human language.
C
External footprint and entity alignment
Relevant directories, authoritative mentions, coordination with independent sources. When the model checks brand claims — it has something to lean on.
D
Research with real people
Surveys, focus groups, checks of how the brand is perceived live, initiating public discussions with neutral wording. The network has 100,000+ real people — each with their own device, not bots and not invented personas.

Plus cross-cutting layers that run through every direction: execution across multiple markets and languages, partner coordination (PR, development, localization), repeat validation through the engine. The full map is on the "Capabilities" page.

More on the directions

Three formats with a clear entry point.

The most common scenario: start with an express report and then decide whether a specialist consultation and work plan are needed, or whether the report is enough. Some projects move straight into ongoing operations.

$200 — diagnosis and plan

Specialist consultation and work plan

An hour to an hour and a half conversation, context review, priority setting, and a 30-60-90 day work plan with a clear first step.

Individual

Ongoing operations

Several work directions as an ongoing function. One calendar, one point of responsibility, regular rechecks through the engine, and a monthly report. Cost is discussed individually.

Compare formats
AI100

If you need an independent benchmark.

AI100 is a standalone study of how brands appear in AI system answers. The full methodology report costs $999. If the client needs a separate measurement they can use in a conversation with investors or the internal team, we can recommend AI100 as an independent layer. It is a separate product with its own methodology and reporting.

Governed execution, clear boundaries.

We document what we do. Sensitive tasks go through manual review before launch. We sell research and advisory work, not engagement — no bots, no fake reviews, no purchased likes, follows, votes, or traffic. We connect real people from our network only to transparent work: surveys, focus groups, perception checks; presenting participants as independent experts is outside what we do. The full position is on the "Approach" page.

Who this fits best.

Most useful where visibility has already become a structural input, not a line item in marketing.

  • Brands across multiple language markets with differences in how they are understood.
  • Technology companies, research labs, telecom — where machine-readable form matters as much as human-readable form.
  • High-trust service businesses — medical technology, legal practices, educational institutions.
  • Regulated industries — we only enter after an individual review of the jurisdiction and registration form.
  • Teams that are repositioning or entering a new market and want to rebuild visibility before scaling.

Where we usually are not a fit:

  • Requests for guaranteed specific positions or citations — we do not control what models show.
  • Political, government, or advocacy projects — we refuse without exceptions.
  • Requests for one point tactic with no interest in analyzing the situation — there are SEO agencies and content studios that do this better than we do.
  • Teams that treat documentation and manual review as extra overhead rather than part of the product.

If the brand is already getting lost in AI results — we will see where and why.

$20 for an express report. A couple of hours of live review if needed. Then the client decides.

Get an express audit — $20Talk to a specialist — $200