The AI Visibility Operator

The power of technology.
Human expertise.
Action for your brand.

Our experts analyze how AI engines present your brand, recommend a strategy aligned with your reputation, competition, pricing, sales and marketing stakes, then execute the actions with our proprietary technology.

  • Every buying question tracked
  • Named, source only or absent, engine by engine
  • The questions where a competitor is cited instead of you

Our approach

Experts first. Technology that makes them faster. Execution you can verify.

01 · Our experts

They interpret, arbitrate and recommend.

They read the signals, connect each gap to your business stakes and build the action plan.

Sample recommendation
"Start with the integration questions: the brand is absent there, and a third-party comparison feeds the competitor cited in its place."

A decision made from the measured corpus, not from an automated score.

02 · Our technology

5 proprietary modules, in production.

They measure, audit, prioritize, produce and re-measure, so our experts decide quickly and on facts.

See the 5 modules ↓

03 · Our execution

Deliverables and assets, not one more dashboard.

What you receive, every cycle:

  • The baseline measurement and the raw answers
  • The technical audit and ranked fixes
  • The prioritized action plan
  • The assets, produced, checked and approved
  • The re-measurement and the report

Our impact

Five areas where AI answers weigh on your results.

Our expertsdecide + Our proprietary technologymeasures, prioritizes, produces

A tech-enabled service: every recommendation is made by an expert, on facts our own modules have measured.

  1. 01

    Reputation

    What do AI engines say about you when a buyer asks?

    We read the tone of every answer that names you, spot errors and unfavorable narratives, and work on the sources that feed them.

    Our experts decide what needs correcting and howOur technology: the measurement module classifies the tone of every answer

    114 positive answers, 13 neutral, 0 negative, out of 127 classifiedbaseline measurement, B2B SaaS case
  2. 02

    Competitive positioning

    Do you make the shortlist against your competitors?

    We measure who gets named instead of you, on which questions and through which sources, then we target the questions where the gap is decided.

    Our experts choose the battles worth fightingOur technology: extraction and arbitration of named brands, share of voice

    #10 → #6 among cited competitorsshare of voice 3.29% → 4.42%
  3. 03

    Value perception and pricing

    How do AI engines describe your offer, your price, your alternatives?

    We analyze answers to comparison and alternatives questions, and we produce the assets that explain your value in the terms AI engines reuse.

    Our experts shape the value narrative to establishOur technology: answers read by intent family

    Measured on your "alternatives and comparisons" questions
  4. 04

    Sales

    Are you recommended on the questions that come right before a purchase?

    We target late-stage questions, where the list of vendors to contact takes shape, and we produce the assets AI engines cite.

    Our experts map each question to a buying stageOur technology: the decision module ranks questions by stake

    11 → 63 answers citing the brandon the 13 targeted questions, 260 answers
  5. 05

    Marketing

    Where should you invest in assets to be picked up by AI engines?

    We identify the formats and sources that matter, then our teams produce, check and publish.

    Our experts brief and check every assetOur technology: the production module, and tracking of cited assets

    54 answers cite the 3 assets producedclient site: #5 → #2 cited source

Figures: US B2B SaaS vendor (anonymized), measurements of August 9, 2026 and September 22, 2026. See the case →

Demo · one buying question, end to end

From absent to shortlisted, step by step.

01

Measure

A buyer asks which EDR to choose for a mid-size company. The AI shortlists three vendors. Your brand is not there, and your competitors are the ones cited.

02

Diagnose

Our experts cross-check the cited sources, the leading competitors and the technical audit, and trace each gap to its cause.

03

Decide

They rank the opportunities and set the first action.

04

Produce

Our teams write the asset that answers the question precisely, check it, and submit it to you before publication.

05

Re-measure

We published a comparison; at the next measurement, we observed the brand in the shortlist, with that comparison cited as a source. Both measurements follow the same protocol.

AI assistant · buying question demo data

"Which EDR solution for a mid-size company?"

  1. 01 Vendor A
  2. 02 Vendor B
  3. 03 Vendor C

Demo brand: absent from the answer

source · third-party-comparison.comsource · specialist forum

Deliverable excerpt · diagnosis demo data

GapObserved cause
Absent on "EDR for mid-size companies"Competitor cited via a third-party comparison
Source only on "compliance-ready EDR"Compliance page hard for AI engines to read
Absent on "outsourced SOC"No owned source on the topic

Built by our experts from the measurement and the technical audit.

Deliverable excerpt · action plan demo data

GapPriorityAction
Absent on "EDR for mid-size companies"1Comparison page + third-party profile
Source only on "compliance-ready EDR"2Technical fix + pillar page
Absent on "outsourced SOC"3Answer-first article

Prioritized by our experts against your goals, with the decision module.

Production brief demo data

Target question Which EDR solution for a mid-size company?

Format Comparison page · 3 credits

Angle Verifiable selection criteria, citable sources, answer at the top of the page

Checks Accuracy · sources · brand voice · markup

  1. Brief
  2. Writing
  3. Quality control
  4. Your approval
  5. Published

"Which EDR solution for a mid-size company?" · next measurement

  1. 01 Vendor A
  2. 02 Demo brand
  3. 03 Vendor B

source · your comparison

The platform

Four capabilities, linked by one thread.

01 · Intelligence

Know where you stand

What AI engines answer about your market, whom they cite instead of you, on which buying questions and from which sources.

02 · Diagnosis & decision

Know what to do next

What keeps AI engines from citing you, and the action plan our experts prioritize against your goals.

Technical audit · excerpt demo data

68/100
  • Key pages unreadable without JavaScript
  • Incomplete structured data
  • AI crawlers allowed
  • llms.txt present

Fixes ranked by impact, built into the action plan.

03 · Activation

Do the work

Our teams produce the assets most likely to move the answer, with quality control and transparent credits.

04 · Impact

See what changed

The same measurement, run again. What moved, what did not, with the raw answers.

What sets us apart

A tool shows you where you stand. We take care of what comes next.

AI visibility tracking tools are improving fast, and some offer agents. Our difference lies in what our experts take on, and in how we measure.

A tracking toolZivRank
MeasurementObserved answersA fixed, published protocol, frozen models, raw answers delivered
DiagnosisDashboardsExperts who trace each gap to its cause: sources, competitors, technical
DecisionGeneric recommendationsAn action plan prioritized against your goals: reputation, competition, pricing, sales, marketing
ProductionDo it yourself, or with agentsProduced by our teams, checked, approved by you, paid in transparent credits
OutcomeA visibility curveThe same measurement run again, a noise floor set before the result, and what did not move published
SupportSelf-serviceExperts who present the results and adjust the plan

03 · Activation · ZivRank Engine

The work gets done. By our teams, with our modules.

From expert recommendation to published asset, every step has an owner. The production steps, the formats and their credit cost are detailed on the ZivRank Engine page.

Discover ZivRank Engine →Subscription + credits: see the plans →

Under the hood

5 proprietary modules, serving our experts.

Our internal building blocks, not to be confused with the AI engines we measure (ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews).

  1. 01Measurement module

    Asks AI engines your buying questions, collects their answers and sources, and classifies every answer.

    In production
  2. 02Technical audit module

    Checks what prevents AI engines from reading, understanding and citing your site.

    In production
  3. 03Decision module

    Ranks the gaps, filters out noise and proposes the actions to take first.

    In production
  4. 04Production module

    Briefs, writes and checks assets with our experts, from brief to publishable asset.

    In production
  5. 05Contribution module

    Re-measures with the same protocol and links, over time, what was published to what moved.

    In production

Measurement

A measurement you can rerun, with its limits written down.

Same questions, same engines, same models from one measurement to the next, with a noise floor set in advance: the full protocol is published. Read the measurement protocol →

128 → 175

answers naming the brand, out of 1,000

Measurements of August 9, 2026 and September 22, 2026 · US B2B SaaS vendor (anonymized)

54

answers citing the assets produced by our teams

Measurement of September 22, 2026 · 3 assets published

See the results →

Let's see what AI engines say about your brand.

Is ZivRank software or a service?

Both. Our experts analyze, recommend and execute; our proprietary technology measures, audits, prioritizes and speeds up production; the console lets you follow the measurements, the assets and how things evolve.

What is in the action plan?

For each opportunity: the observed gap, its likely cause (sources, competitors, technical), the priority and the proposed action, with the asset to produce. Our experts build it against your goals.

How do you know whether the actions worked?

We run exactly the same measurement again, with the same questions and the same models, and compare. We document what moved as well as what did not, without claiming causality the data cannot establish. The protocol and its noise floor are detailed on the Methodology page.