Trusted by operators at
The Visibility Architecture
$10,000 one-time. I build the AI-search visibility system that measures where your company appears across ChatGPT, Claude, Gemini, and Perplexity, then turns the gaps into a content and technical roadmap.
Built for Series A B2B AI SaaS teams who know search behavior is moving from Google pages to model answers.
Currently installing 2 Visibility Architectures this quarter.
Trusted by operators at
02 : The AI-Search Shift
Buyers no longer need ten blue links to build a shortlist. They ask a model for vendors, risks, comparisons, implementation paths, and category context. The answer may decide who gets remembered.
It is whether ChatGPT, Claude, Gemini, or Perplexity names you, compares you fairly, and remembers the category you belong in.
A buyer can ask for "best AI infrastructure vendors for Series A teams" and get a confident shortlist without ever touching your site.
Models need structured proof, crawlable content, comparative clarity, category language, and repeated authority signals they can retrieve.
The Visibility Architecture measures your AI-search Share of Voice, finds the prompts where competitors win, and turns those gaps into content and technical actions before the market standardizes around someone else.
AI-search will overtake Google search for B2B vendor discovery within 24 months. Your category is already 5-15% there. The teams installing AI-search visibility infrastructure now will own the shortlist when the curve flips.
04 : The Mechanism
The work starts with the searches your buyers actually run, not with generic keywords. Then the system measures model answers and turns them into a concrete visibility roadmap.
Step 01
Prompt Map
I build the buyer-intent prompt set: category searches, vendor comparisons, implementation questions, risk checks, alternatives, and internal-buy-in queries.
Step 02
Model Run
The system checks how ChatGPT, Claude, Gemini, Perplexity, and available AI-search surfaces answer those prompts across repeated runs.
Step 03
Gap Diagnosis
I score whether you appear, where competitors appear, what claims models repeat, where hallucinations happen, and which sources seem to shape the answer.
Step 04
Roadmap Loop
The output becomes a content, schema, crawler-accessibility, and category-proof roadmap, then gets monitored on a cadence.
05 : Ops Demo
The dashboard is built around buyer-intent prompts across ChatGPT, Claude, and Perplexity. Instead of pretending a pre-measurement score exists, the baseline classifies visibility into capability tiers.
06 : THE DELIVERABLES
These are the deliverables inside the $10,000 Visibility Architecture build.
01
The monitoring system that runs buyer-intent prompts and captures how AI-search surfaces describe your category, company, and competitors.
02
Capability-tier scoring across ChatGPT, Claude, Gemini, Perplexity, and other available answer surfaces.
03
A recurring check for whether models recommend you accurately, omit you, misstate your product, or invent damaging context.
04
A diagnosis of the pages, proof assets, comparisons, schemas, and category content needed to influence future model answers.
05
Prompt sets mapped to problem-aware, solution-aware, vendor-comparison, security, implementation, and internal-buy-in buyer stages.
06
A prioritized roadmap that turns weak prompts into content briefs, technical fixes, and proof assets.
07
A crawlability review covering robots.txt, llms.txt, structured data, page clarity, and AI crawler accessibility.
08
The first measurement readout with prompt coverage, model-level gaps, competitor appearances, and capability-tier visibility.
This is not SEO consulting, AI prompt training, or generic share-of-voice reporting. It's the technical and content infrastructure for AI-search visibility, installed once.
07 : Proof
The model has to understand the company, but the buyer still has to trust the answer. The public proof shows technical translation, sales context, and voice discipline. The private proof stays locked.
Revenue
"Sebastian is a sage at his craft, just as I am at mine. He is always contributing with insight in the Sales Rocket Mastermind."
Doru Pelivan
Founder
eduKIWI (8-figure EdTech)
Growth
"Sebastian captured exactly the thinking style and writing voice I was looking for. My Udemy courses increased ratings from 4.6 to 4.8."
Jonas Schmedtmann
Instructor
Udemy
Engineering
"Sebastian is obviously a highly skilled and knowledgeable web developer. He delivered one of our biggest projects in just the right amount of time."
Martin Aranovitch
Manager
WPMU Dev
Tech
"I trust in Sebastian's great work ethic and capacity. Communicating with him is always straightforward."
Andrew Radulescu
CEO
Tribus Technologies
Strategy
"Sebastian has achieved some of the best show-up rates on my sales team. A very professional voice."
Roxana Borz
7-figure Coach
Manifestation Academy
08 : Investment
A one-time visibility architecture for teams that want measured AI-search exposure before competitors become the default answer.
The Visibility Architecture
$10K one-time ยท AI-search visibility build
$10,000
$10,000 one-time. Includes the LLM discovery engine, multi-surface Share of Voice scoring, hallucination monitoring, content gap analyzer, prompt map, roadmap generator, and AI-crawler technical audit.
BOOK A 30-MIN AUDIT OF YOUR AI-SEARCH VISIBILITY →Verified Share of Voice numbers are baselined at engagement kickoff and reported monthly thereafter.
09 : Frequently Asked Questions
I build a buyer-intent prompt set, run it across AI-search surfaces such as ChatGPT, Claude, Gemini, and Perplexity, then score whether your company appears, how prominently it appears, and which competitors are recommended instead.
The exact prompt volume and measurement window should be set from the category and buyer motion. Verified Share of Voice is baselined at engagement kickoff and reported monthly thereafter.
Winning is not simply being mentioned once. A useful score looks at recommendation frequency, position in the answer, accuracy, sentiment, comparison quality, and whether the model ties your company to the right buying use case.
The first baseline uses capability tiers: Tier A means repeated verified mentions, Tier B means partial visibility, and Tier C means competitors rank while you are absent.
The initial build establishes the baseline. After that, the right cadence depends on how quickly your category moves, how often competitors publish, and how aggressively your team executes the roadmap.
For a fast-moving AI category, monthly monitoring is usually the minimum worth considering. The dashboard should show movement by tier before it claims precision by score.
Model answers will move. That is the reason the architecture is a monitoring loop, not a one-time report. New model releases, retrieval changes, and search integrations can alter which sources get surfaced.
The system is designed to detect movement, identify whether the shift helped or hurt visibility, and turn the change into new content or technical actions.
Both matter. The best answer is built from crawlable proof: clear pages, structured data, accessible robots rules, llms.txt, comparison context, and public claims that models can retrieve without guessing.
The build includes an AI-crawler technical accessibility audit so the roadmap is not trapped at the copy level.
10 : Book The Consultation
Bring your category, competitors, current search assets, sitemap, and the buyer questions that decide shortlists. I will show you where AI-search visibility is likely leaking and what should be measured first.
BOOK A 30-MIN AUDIT OF YOUR AI-SEARCH VISIBILITY →30 minutes. No pitch. Just the AI-search visibility diagnosis.