Best AI/GEO Agencies: How to Choose the Right Partner

A GEO (Generative Engine Optimization) agency optimizes your site to be cited inside AI search engines — ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews. Their work product is measurable citation-rate lift across the prompts buyers actually use. An SEO agency optimizes for Google search ranking — backlinks, keyword density, page speed, click-through rate. Many SEO agencies have started using GEO vocabulary in 2026, but their technical playbook hasn't changed. The honest test: ask either type for citation-rate data from a real engagement. A real GEO agency has it; a relabelled SEO agency usually doesn't.

Evaluate against six criteria: (1) real citation-rate data from a documented engagement, (2) technical depth — can they walk through a deployed entity graph and explain their schema choices, (3) bilingual coverage — English plus the local language(s) your buyers search in, (4) reporting transparency — you should see per-prompt and per-engine breakdowns, not just a headline number, (5) integration with downstream automation so AI traffic actually converts, (6) pricing model — fixed retainer with shipped artifacts is the healthiest shape. Walk away from agencies that can't show you their own llms.txt or their own schema graph.

AI/GEO engagements typically price between $2,000 and $7,000 per month for ongoing monitoring + content + schema work, with a one-time setup fee of $4,000–$11,000 covering the initial audit, entity graph rebuild, schema deployment at scale, and the first authority pillar page. Engagements priced under $1,500/month tend to be content-only offerings without the technical infrastructure work that actually moves citation rate. Pricing scales with content library size, language coverage, and number of engines monitored.

Early movement usually comes from technical accessibility, entity clarity, improved internal linking, structured data validation, and stronger source pages. Timing varies by engine, crawl frequency, site authority, and baseline visibility. Compound results typically build between weeks 6 and 12 as engines re-crawl and validate the entity graph — but specific multiples aren't guaranteed.

Build in-house if you have a senior technical SEO who can also write JSON-LD by hand, configure crawler permissions, and stay current with schema.org evolution — and if you can give them dedicated time. Most companies don't have that profile and end up with a part-time effort that takes 9–12 months to ship what a focused agency ships in 8 weeks. Hire when speed-to-citation matters and you want measurable monthly progress. The break-even point is usually around 18 months — beyond that, in-house can be cheaper if the role is well-staffed.

Two differences. First, our process is an 8-step productized methodology (prompt market mapping → competitor audit → entity graph repair → schema deployment → authority pages → crawler accessibility review → citation-rate monitoring → lead automation integration), shipped with named artifacts at each step — not a freelance content offering wrapped in GEO vocabulary. Second, we integrate the AI-driven traffic into the same process automation infrastructure we build for our automation clients, so visibility actually converts instead of dying in a contact form. Our Fershteyn Law engagement (citation rate 16.1% → 62% in 8 weeks across 30 prompts, three engines) is documented publicly with the full teardown.