The AI platform Media Production and Publishing uses to get recommended on
Your work is what the engines read, and increasingly what they repeat without sending anyone back. LBOX measures where your reporting is being used, which outlets get named instead, and builds the evidence to change the terms.
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 Media Production and Publishing different
Not general marketing advice. These are the constraints your category actually operates under.
The answer replaces the click your business model depends on.
A reader asking about a story gets a summary drawn from your reporting. The question is answered, the page is never opened, and the advertising and subscription value of that reader goes nowhere. You supplied the product and someone else delivered it.
Attribution disappears exactly where it matters most.
The investigations and exclusives that cost the most are the ones most likely to be summarised without a name attached. Your masthead is the asset, and it is being stripped off the work in the moment the work is most useful.
Your archive is a strength the engines flatten.
Decades of coverage is real authority, but to a model it is undifferentiated text. An outlet that has covered a subject for thirty years reads the same as one that published on it last week.
Syndication multiplies the versions and dilutes the original.
Wire pickups and partner republishing put many near-identical copies on the web. The engines may quote any of them, and often the one that gets cited is not the one with your name on it.
You are the source the engines quote most and the destination they send to least
Publishing sits in a position no other industry on this site occupies. You are not trying to get into the answer, you are already in it: your reporting is what the models read, and frequently what they paraphrase. The problem is the second half, where the traffic that used to pay for the reporting does not arrive. That asymmetry is uncomfortable, but it is also leverage, and it is measurable. Knowing which of your work is being used, by which engines, and whether your name survives the summary, turns a vague grievance about AI into a specific record. That record is what a licensing conversation, a syndication renegotiation or a policy position has to be built on, and almost nobody in the industry currently has one.
What you get back
The console, measuring a company in Media Production and Publishing 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 outlets the engines name
Visibility and position on the unbranded where-should-I-read-about questions your readers ask, measured per engine.
- Ranked against the outlets 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 editorial team.
- Scored against your beats and topics, not a generic SEO checklist
- Nothing publishes without your sign off
The worklist
Where you disappear as the reader gets closer to reading the source
Presence falls away as intent rises. The where-should-I-read-about questions are the ones that convert, and the ones the aggregators win.
- Visibility split by where the question sits in the journey
- Names the stage that costs you the reader
Visibility by buying stage
where you show up in the journeyThe sources the engines trust about publishers
Community threads, reference sites and wires decide which outlet gets named, and a wire pickup of your own story often gets the citation instead of you.
- 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
658 citationsThe program for Media Production and Publishing
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 titles today, through the engines own APIs
- The questions your readers actually ask, mapped by beat, topic and story
- Where your reporting is being used and whether your name survives the summary
- Whether the engines attribute your work and your titles correctly
- Which sources the engines cite on your beats, and which of those you control
- Story, topic and archive pages built so the engines can read and attribute 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.