The AI platform IT Services and IT Consulting uses to get recommended on
Buyers ask a model to shortlist providers by stack, certification and security posture. LBOX measures what the engines say about you, shows who they name instead, and builds the evidence that changes it.
Measured across
Perplexity
Gemini
Google AI
Claude
Copilot
Meta
DeepSeekGrok... and moreEvery one of them is competing for the same answer. One name comes back when a buyer asks.
What makes IT Services and IT Consulting different
Not general marketing advice. These are the constraints your category actually operates under.
The shortlist is built before procurement opens.
Who should we use for a migration, a managed service, a platform build. A model returns three or four names, and by the time an RFP exists the field has already been narrowed. You never see the opportunity you were left out of.
Certifications and partner tiers get stated wrong.
Partner status is earned, audited and contractually described. A model that awards you a tier you do not hold, or overlooks one you do, is creating both a misrepresentation you did not make and a competitive disadvantage you cannot see.
Security posture is answered from whatever is readable.
Buyers ask about certifications, data residency and incident history before they ask about price. Those answers get assembled from old pages and third-party write-ups, and in this category a wrong answer ends the evaluation silently.
Marketplaces and vendor directories answer in your place.
The hyperscaler marketplaces and review directories are structured, dense and constantly updated, which is exactly what an engine prefers to read. Your own case studies are none of those things.
One shortlist place is years of revenue, because nobody switches
Managed services and systems integration are unusual in how long a win lasts. Contracts run for years, switching costs are severe, and incumbents are rarely displaced without a crisis. That makes each individual shortlist decision worth far more than its size suggests, and it makes exclusion far more expensive: losing a place on a three-name list is not losing one deal, it is being locked out of an account for the length of somebody else contract. The compounding runs the other way too. Being named consistently is how a firm becomes the default answer in its niche, and a default is very hard to dislodge once a model has settled on it.
What you get back
The console, measuring a company in IT Services and IT Consulting against the questions its buyers ask. Every brand named, every domain cited, every engine separately.
A worked example on an illustrative company, shown to display the console. Your own numbers come from measuring your questions through the engines’ own APIs.
See which providers the engines name
Visibility and position on the unbranded who-should-we-use questions your buyers ask, measured per engine.
- Ranked against the providers the engines actually named
- See where a model reads your pages without naming you
You against the field, engine by engine
unbranded questionsTurn what the answers get wrong into work that ships
Findings arrive as a worklist sorted by who can act: what LBOX writes, what needs your decision, what needs your solutions team.
- Scored against your stack and certifications, not a generic SEO checklist
- Nothing publishes without your sign off
The worklist
Where you disappear as the buyer gets closer to shortlisting
Presence falls away as intent rises. The who-should-we-use questions are the ones that convert, and the ones the marketplaces win.
- Visibility split by where the question sits in the journey
- Names the stage that costs you the shortlist place
Visibility by buying stage
where you show up in the journeyThe sources the engines trust about IT providers
Review directories and vendor marketplaces decide which providers get named, because they are structured and current in a way case studies are not.
- Owned versus earned, so you know what to build and what to earn
- Every citation traced to the answer it supported
Which domains the engines cite
638 citationsThe program for IT Services and IT Consulting
Everything below is included. Measured through the engines’ own APIs, so the same questions can be asked again and the result checked.
- Measure what every major AI engine says about your firm today, through the engines own APIs
- The questions your buyers actually ask, mapped by stack, service model and sector
- Where a marketplace or review directory is answering in your place
- Whether the engines state your certifications, partner tiers and security posture correctly
- Which sources the engines cite for your stack, and which of those you control
- Service, stack and certification pages built so the engines can read and quote them accurately
- Re-measurement on the same questions, so the change is provable rather than asserted
What this does not show: what any individual user saw. LBOX measures what the engines answer through their own APIs, which is repeatable and checkable. It is not a record of any one person’s session, and it does not predict revenue.