GEO agency shaping how AI models describe your brand

What GEO is, precisely

GEO (generative engine optimization) is the practice of influencing what a generative model says about your brand and category. The surface is the generated text itself. The unit of success is representation: are you named in the shortlist, and is the description of your product, category, and pricing correct.

That is a different job from AEO. AEO structures your own pages so a model can lift and cite a clean answer. GEO works on the wider evidence base a model retrieves and generalizes from, most of which sits on other people's sites.

• Brand representation audit: verbatim model output across ChatGPT, Perplexity, Gemini, and AI Overviews
• Entity consistency across your site, schema, directories, review profiles, and social bios
• Third-party corpus building: review coverage, category roundups, comparison content, credible community presence
• Competitor displacement mapping on commercial shortlist prompts
• Correction workflow for outdated pricing, sunset features, and abandoned positioning
• Monthly share of voice and sentiment reporting on a stable prompt set

How we run GEO

We start by listening. One fixed prompt set, run across the major engines, captured verbatim. That gives two scorecards from one pass: whether you are cited (AEO) and whether you are named and described correctly (GEO).

Then we fix entities, because inconsistent naming undermines everything downstream. After that we work the corpus in priority order, targeting the specific third-party sources the models are already quoting in your baseline rather than a generic link list.

GEO, AEO, and SEO run as one program

These three disciplines share a prompt set, a content pipeline, and an entity graph. Splitting them across vendors doubles the cost and halves the signal, because the same page and the same schema serve all three outcomes.

That is why GEO is included in every Momentence tier rather than sold as an upsell. The tier determines depth: how many prompts we track, how much off-site placement work we run, and how granular the reporting gets.

Honest timelines

Entity and consistency fixes can change model output inside 30 to 60 days, because they resolve ambiguity rather than needing new sources. Displacing an incumbent in a competitive shortlist prompt is a 6 to 12 month program, since it depends on third-party sources publishing and refreshing.

Model output is non-deterministic and shifts between runs and versions. Anyone guaranteeing a specific phrasing or placement is selling something they do not control. We report the trend on a stable prompt set and attach the raw output.

Pricing, in public

Every engagement is published pricing on a 6-month minimum: Ignite at $6,500/mo, Momentum at $14,000/mo, Dominate at $28,000/mo, and Custom starting at $45,000/mo for a dedicated pod. You will know what this costs before you ever get on a call.