A ChatGPT & Perplexity optimisation agency
that gets your brand found and named inside the answers.

The technical foundation overlaps, and we don't pretend otherwise. What's different is the unit of competition. Conventional SEO optimises a page to rank against a query. ChatGPT and Perplexity retrieve a handful of passages and write an answer from them, then cite the ones they used. Ranking well gets you considered, it doesn't decide who gets quoted.

That takes passage-level content engineering, entity work across every source that mentions your brand, and citation sampling on a schedule, since the answers change from one query to the next. A content writer or a schema plugin covers a piece of that. It doesn't cover the whole discipline.

Whoever is already being cited for your category's questions keeps accumulating the coverage and corroboration that earned them that spot. An established citation is hard to displace once a model has effectively learned to trust that source for the question. Waiting doesn't preserve your position, it hands the accumulation period to whoever starts first.

This is also why the audit is free: you can see exactly where you and your competitors stand today before deciding anything, rather than guessing at the cost of delay.

We implement them. Fixes go into your codebase or CMS by the same engineers who ship production work, then each one is checked and re-sampled against the prompt set before it's marked done.

A findings document with no implementation path is the most common reason this kind of work stalls, because it ends up queued behind other priorities and ages out before it ships. We'd rather ship it and show you the citation count move.

No, and anyone telling you it does is overselling it. A language model reads the text of a page, not its schema markup. What schema does is remove ambiguity for the systems upstream of the model, which improves how cleanly a page gets parsed and considered.

We treat it as accuracy infrastructure, not a citation lever, and we say so plainly because it's the kind of overclaim that burns trust with a technical buyer.

With a fixed prompt set and repeated sampling. The same prompt run five times can cite five different sets of sources, so one query proves very little. We build the prompt list from real buying questions, run it on a schedule in both platforms, and record how often you appear, whether you're named or paraphrased, and who else is in the answer.

If you're comparing agencies for this work, ask for the prompt list and the baseline. Anyone doing it seriously has both.

Perplexity retrieves at query time, so a corrected page can start appearing within weeks of being crawled. ChatGPT's citation set is more conservative and tends to track off-site coverage, so it takes longer. Entity and authority work is the slowest part, measured in months, because it depends on third-party sources updating their own records.

We record the baseline in week one specifically so the change is visible on your own timeline, not argued about later.