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Syndral

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AI Visibility Agency

Syndral is an AI Visibility agency. We help reputation-driven businesses get named and recommended when their buyers ask AI tools like ChatGPT, Gemini, and Perplexity who to trust. The discipline is called Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO). Syndral was founded in 2026 by Kevin Pantanella and his team, building on twelve years of web agency work at Suzaku Productions.

  • Min project size
    $1,000+
  • Hourly rate
    $100 - $149 / hr
  • Employees
    2 - 9
  • Locations
    Bangkok, Thailand
  • Year founded
    Founded 2026

Overview by:

Reviewer avatar
Kevin Pantanella
Founder About the Team

1 Locations

  • Bangkok , Thailand

Service Lines
Search Engine Optimization
100%
Select Focus Area
SEO Focus
Generative Engine Optimization
60%
Content development
20%
Technical SEO
20%
Industries
Business services
30%
Legal
30%
Medical
30%
Other industries
10%
Clients

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Our Story

For twelve years, at Suzaku Productions, we built websites that brought in traffic and converted it into customers. The model worked. Then, recently, it stopped. The same sites that ranked and converted for years started losing traffic, and the leads dried up. We had a choice: pretend it was a temporary dip, or find out what had actually changed. We dug in. Buyers had quietly changed how they search. They ask an assistant, and it names a few companies. Syndral makes sure yours is one.

Meet the Team

Kevin Pantanella

Kevin PantanellaFounder

Kevin founded Suzaku Productions in Bangkok in 2014 and built more than 100 websites across Europe and Asia. He started Syndral in 2026, after watching search traffic fall on sites that had not got worse, and now measures what AI assistants say.

What Sets Us Apart

We measure before we promise

Every engagement opens with a Diagnostic, not a proposal. We run a frozen set of real buying questions across the AI assistants your market uses, and record what is actually said about you. Only then do we tell you what to change.

We show the raw answers

Every number we report comes with the answer it was read from. If an assistant named a competitor instead of you, you see the sentence. Nothing is summarised into a score you cannot check.

The same instrument, twice

The questions are frozen at the start and re-run ninety days later, on the same platforms, under the same conditions. That is what makes the second measurement comparable to the first, instead of a new claim.

Tools and Technology

Slack
Google Meet
Notion
Google Drive
Google Docs
Google Sheets
Google Slides
GitHub
Vercel
Google Workspace

Commonly Asked Questions

We start from the questions your buyers would actually ask an assistant, twelve of them, in their words rather than ours, and we freeze that set. Each question is put to ChatGPT, Gemini, Perplexity and Claude, and each one is asked at least twice, and up to five times, because an assistant does not reliably give the same answer twice. Every answer is recorded as it came out. The report then tells you how often you were named, how often a competitor was named instead, and what is causing it, with the raw answers attached so you can check any figure against the sentence it came from.

SEO optimises for a results page of ten links, where the reader picks. An assistant returns one answer naming two or three companies, and the chain that builds that answer is not the chain that ranks a search result. In our own tests, the same question asked on different AI surfaces returned different sets of companies, which is why each surface is measured on its own rather than treated as a proxy for the others. The work that follows is different too: the goal is not to rank a page, it is to be the company an assistant names, and to be a source it can quote.

ChatGPT, Gemini, Perplexity and Claude, each reported separately, because a company can be named on one and absent on another. Depth is not identical everywhere, since the platforms do not all allow the same number of runs, and the report says so rather than smoothing it over. Surfaces that publish no data of their own, such as Siri, are marked as not measured. We would rather leave a gap visible than fill it with an estimate.

We agree the twelve questions your buyers actually ask, in their words, and we freeze them. Nothing in that set changes afterwards, because a question swapped halfway makes the ninety-day comparison meaningless. The competitors we track and the market being measured are frozen at the same moment, for the same reason. Then we run the set, capture every answer, and write the report from what was recorded. Ninety days later the same questions are run again, on the same platforms, so you can see movement instead of taking our word for it.

Few, and on purpose. Every engagement starts with a Diagnostic: we take twelve real questions your buyers would ask an AI assistant, such as who they should hire for a given job, and we run them across ChatGPT, Gemini, Perplexity and Claude. Every answer is recorded as it came out. That capture is done by a person rather than by a dashboard, and reading it back is slow work. It is also what lets us show you the sentence behind every number in the report, instead of a score you are asked to trust.

Locations (1)

139 Blue Chips Building, Room S-607, 6th Floor, Soi Sukhumvit 63 (Thong Lor 10), Sukhumvit Road, Khlong Tan Nuea Bangkok, Thailand 10110

2 - 5

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