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AVE Studio · AI Visibility Engineering

TIER 1 · BE SEEN

A4 · Stage 2 — Fix: the fix, in code

Gap Closure · GEO an executable fix package

Generative Engine Optimization

Being found, included and cited when an AI generates an answer — at answer time, from the live web.

Generative Engine Optimization: the definition
— visibility in AI answers

You have the diagnosis, but no capacity to build the fixes. The Gap Closure doesn't hand you another advice list — it delivers ready-to-insert code and copy.

The machine-equity loop — Gap Closure

  1. 1 · MEASURE — “Where do I stand today?” Per engine, with a range (Citation Tracker, Selector)
  2. 2 · FIX — “Why do they skip me?” Page by page, then fixed in code (Gap Analysis, Gap Closure)
  3. 3 · ANCHOR — “Where does the machine learn about me?” An unambiguous entity, present where models learn (Entity Anchor, Corpus Campaign)
  4. 4 · PROVE ↺ — “Did it move, and what did it bring?” Closed-book baseline and the delta at every new model generation (Model Memory Audit, Release Audit)
→ AI TRANSACTION — when the agent buys (agentic commerce · roadmap)

KG Doctor and the Claim Coherence Engine — the studio's own instruments — serve the entire loop.

Execution order:
A1A2A3A4
→ sequential
AVE Studio doesn't run short-term campaigns: we build our partners'
Machine equity

Machine equity is the business asset that arises from AI systems being able to recognize, understand, recall, recommend — and, on a user's behalf, transact with — a brand. Composed of three layers: rented reach (retrieval visibility), owned memory (trained model recall), and machine buyability (agent-side transactability). Measured honestly only as a portfolio of ranged, per-layer metrics — never as a single blended score.

Machine equity: the definition
, across model generations.
The problem

Most audits end exactly where implementation should begin: you get a list of findings, and the fixes don't materialize for months. The Gap Closure turns the Gap Analysis results into an immediately executable package. It produces structured-data code — JSON-LD —, ready FAQ copy, an llms.txt file, outlines for new pages, and modifications fitted to your live site's HTML, ready to paste in.

What you receive: the anatomy of a task card
Illustrative
Task: FAQ block for the service page
EFFORT: ~1 HOUR
WHAT
A ready question-and-answer block for your buyers' three most frequent questions.
HOW
Insert the attached copy block at the marked point on the page. Missing company data is marked ‹TO BE FILLED›.
WHY
This change addresses two target questions; the pages recommended instead of you measurably use this answer format.
DONE WHEN
The block is live on the production page and appears in the page's raw HTML.

A task card like this is produced for every uncovered gap. You don't get a generic SEO finding — you get a precise instruction: what to build, how to integrate it, how much work it takes, and which buyer questions it addresses.

If the system doesn't know a required piece of data — a company detail, say — a clearly marked fill-in field is left in its place. We don't invent data on your behalf; the system's operating rules rule it out.

The "What the better-performing pages do" section summarizes the measured practice of the pages recommended instead of you: their structured data, content freshness and answer format.

Reports are delivered in Hungarian and English.

◇ marks illustrative data — example readouts, not measured client results.

Behind the service: purpose-built software

Every service runs on an application we built in-house for exactly this job — not manual spreadsheets, not general-purpose tools.

A code-and-copy generation system with a built-in quality gate: a report with an overreaching claim cannot ship, and missing data stays a marked field.

Three separate task lists for the people doing the work

01For the developer

Paste-ready code, structured data, technical fixes and page-level modifications, in separately downloadable files.

02For the site editor

Ready copy blocks, FAQ content and page outlines, fitted to precisely marked places on the page.

03For the marketer

Content and presence tasks with a clear sequence and a concrete execution plan.

Why it's different
01

Executable materials, not generic advice

You get code and copy fitted to your own website's structure. Every file downloads directly from the report.

02

Invented data cannot get in

Unknown data points remain clearly visible fill-in fields. The system's architecture doesn't allow it to fabricate a missing fact.

03

Clear limits and effort estimates

The report states precisely what each task solves and what it doesn't promise. It gives an execution order and estimated effort — not a misleading score.

04

Automated quality check before release

The report cannot be published if it contains an overreaching or disallowed claim. An automated check blocks it.

Frequently asked questions

How much does gap closure cost?

The ready-to-paste deliverable package starts from HUF 195,000 net (approx. €490). If you want us to implement it (done-for-you), that starts from a further HUF 225,000 net (approx. €565): after scoping we quote a fixed price — not an open-ended hourly engagement.

What do I receive?

Ready-to-paste fixes: schema code, FAQ blocks, page outlines, an llms.txt file and a developer task sheet your web partner can execute without further interpretation. We do not hand over advice — we hand over work.

Do I get advice or finished work?

Finished work. In the deliverable package every asset is paste-ready and your team or developer implements it. In the done-for-you variant we touch the code ourselves, at a fixed pre-agreed price. Neither variant creates a months-long retainer dependency.

Why not postpone the fix? A diagnosis expires: measured gaps stay comparable until the next measurement round, after which your competitor's pages and the AI answers have both moved. And while the fix is not shipped, the same questions keep naming someone else every month.