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Strynal, Digital Agency

AI Visibility

Being found, and cited, when the answer comes from a machine.

Discovery is moving from a page of links to a single synthesised answer. We make your brand legible to the models writing those answers: structured, authoritative, and quotable, so that when an LLM or answer engine speaks about your category, it speaks about you, accurately.

What we cover

01

Generative engine optimization (GEO)

Earning presence in AI answers: ChatGPT, Gemini, Perplexity, and AI overviews.

02

Structured data & markup

Schema, entities, and metadata that let a machine parse what you are without guessing.

03

Content for retrieval

Clear, well-sourced, quotable writing: the form models prefer to lift and cite.

04

Entity & knowledge-graph presence

A consistent, corroborated identity across the sources models read to build their picture of you.

05

Answer-engine monitoring

Tracking what the major models say about your brand, and where the account is wrong.

06

Technical SEO foundations

Crawlability, performance, and architecture: the groundwork classic and AI discovery share.

07

Authority & citation strategy

The signals and sources that make a model trust you enough to name you.

08

LLM-readiness audits

A clear read on how visible you are to machines today, and what to fix first.

How we work

We treat the model as a reader. That means writing and structuring content so it can be parsed, trusted, and quoted without distortion, the same clarity that serves a person, made explicit enough for a machine.

Because we also design and build the site, the structure isn't advice we leave behind; it's wired into the markup, the architecture, and the content as it ships. Strategy and implementation are the same engagement.

What it earns

When a buyer asks a model instead of a search bar, the brands it names win the consideration set before a click exists. Being legible to machines is fast becoming table stakes for being found at all.

You leave knowing how the models see you and with the work in place to improve it, structured, monitored, and built to stay accurate as the answers keep changing.

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