About
Who this practice is for
Maryan Polyak works with manufacturing and industrial companies that need their products, capabilities, and applications to be found by commercial buyers. The public name of the practice is Manufacturing Marketing Agency. The focus is firms that make or engineer physical products, including metal structures, facade systems, industrial equipment, engineering systems, and heating equipment.
A manufacturer often has several product lines, several markets, and a sales cycle in which an engineer, a buyer, and a manager all read the same website. If that range is collapsed into one general page, the right inquiry is harder to earn. The same gap appears when a buyer uses a conventional search engine and when an AI assistant retrieves pages and summarizes them.
Long-term work with technical products
The practice rests on about twenty years of SEO, website structure, technical content, and digital marketing for complex B2B products. The usual materials are large catalogs, specifications, differences in application, and documentation that has to stay accurate. The work starts from what the company actually makes and sells, then covers the structure of the website or store, the technical pages, and the promotion around them.
Promotion can include classic SEO, content, paid search, link acquisition, and relevant external references. These are parts of one system. A link and an unlinked mention are different signals. Neither is treated as a guaranteed placement in an AI answer.
SEO as the foundation for AI search
Classic technical SEO remains the foundation. Pages still have to be crawlable and tied to a real product, capability, or application. Semantic architecture, internal links, and the vocabulary of the industry are what make a manufacturing site understandable in ordinary search.
AI search extends that foundation. The same facts are organized so AI systems can read them and accurately cite them when they use a source. This is the work sometimes called Generative Engine Optimization (GEO) and answer-engine optimization (AEO). It is structure that is readable by both search engines and AI systems, including assistants such as ChatGPT, Perplexity, Gemini, and Google AI Overviews.
Those products do not retrieve information in one shared way. A citation or recommendation is not guaranteed. Older projects on this site record the work done at the time. They are evidence of technical marketing practice, not claims of a measured GEO or AEO programme.
How an engagement is organized
An engagement starts from the products, the markets, and the commercial task. Website structure, specifications, applications, and promotion are decided from that. Complex catalogs and long sales cycles are normal in this work, not an edge case. Not every company needs every service at once, and many projects continue for years because the range changes.
The aim is a foundation for visibility in ordinary search and in AI answers: clear catalog structure, verifiable technical content, and a semantic architecture that supports both classic SEO and generative search.