When someone asks an AI who to hire, be the answer.
We structure content, schema markup, third-party sources, and brand entity signals so large language models recommend your business inside the answers they synthesize. This runs as a standalone monthly program; nobody needs to buy our search services first.
A buyer opens ChatGPT and describes their problem. Back comes a paragraph naming two or three companies. No links, no results page. Just a recommendation.
"Your business either appears there or it doesn’t. And unlike a search ranking, there’s no position eleven to console you."
Peer-reviewed, not invented last Tuesday.
Researchers from Princeton and IIT Delhi named and formally defined this practice in a paper presented at KDD 2024, the ACM’s conference on knowledge discovery. They built a benchmark of queries paired with the sources a generative engine draws from, then tested nine content-modification strategies.
Their finding, in their own terms: including citations, quotations, and statistics can boost source visibility by over 40% across various queries. We build on that rather than around it.
The target differs, and so does what leaves the building.
Entity structuring
Your brand needs to exist as a recognizable node, not a string of characters. Consistent naming and explicit relationships to your services, locations, and people, reinforced everywhere.
Schema markup
JSON-LD across page types, organizational and service definitions connected rather than declared in isolation. Structured data tells a machine what your content means.
Content for retrieval
Passage-level independence: each section answers its implied question completely, without needing the paragraph above it. Original data, attributed quotes, sourced statistics.
Third-party presence
Models consume far more than your website. Industry publications, review platforms, and community discussions all feed retrieval. Reddit sits squarely here now.
Digital PR
Not any coverage: coverage in sources these systems already trust and return to.
Link building, re-aimed
Same activity as search, different selection criteria. Here, links build the entity graph supporting your brand’s recognizability.
Carefully, and in the open.
We manage accounts under your brand guidelines and within Reddit’s rules, participating as the business, answering questions where the company has genuine expertise, contributing something a subreddit actually wants.
The alternative, unmarked accounts seeding praise, works until someone screenshots it. Then the client owns a manipulation scandal instead of a citation. Reddit rewards being genuinely worth discussing, which is slower and considerably more durable.
Nearly the same objective. The split is what gets produced.
Frequency, share of voice, sentiment.
We track citation frequency, share of voice against competitors, and sentiment across ChatGPT, Claude, Gemini, Perplexity, Copilot, and Grok, on tooling we built in house, so we aren’t passing a vendor’s dashboard through and calling it a service.
Share of voice is the number that should worry you: how often you surface relative to the alternatives. Sentiment matters because being named unfavorably is worse than absence.
As of early 2026, no major AI platform sells placement inside generative answers. Citations get earned through content quality, structural retrievability, entity clarity, and off-site trust, not budget. That will presumably change. We’d suggest doing the work before that window closes.
About GEO.
How do I check whether AI engines currently mention my brand?
Ask them. Open ChatGPT, Perplexity, Gemini, and Claude and pose the question a buyer would: which companies handle this problem in my situation. Note who appears, in what order, described how, across a dozen phrasings. Manual testing gives a rough baseline within an hour. Systematic tracking requires tooling: hundreds of prompts run consistently over months.
Does GEO work for businesses with no established brand recognition?
It works differently. Models weight specificity heavily, so a narrow operator answering precise questions thoroughly can appear where a broader competitor doesn’t. What newer businesses lack is corroboration: the web of third-party sources confirming they exist. Building that takes time regardless of budget; expect months, not weeks.
Can my competitors sabotage my AI visibility?
Not directly. What they can do is build stronger entity signals and earn corroboration from trusted sources, which pushes you down the recommendation order without touching you. Displacement rather than sabotage. The reverse also holds, which is the entire commercial argument for starting now.
Will optimizing for AI engines hurt my Google rankings?
No, and the reverse tends to hold. Practices that improve citation probability, sourced statistics, attributed expert quotes, direct answers, entity clarity, freshness, mirror what Google’s quality systems already reward. The frameworks converge because both evaluate credibility using similar proxies.
What is passage-level independence and why does it matter?
Models frequently extract individual sections rather than whole pages. A paragraph pulled from the middle arrives without context, so it must make complete sense alone: answer its implied question fully, define its terms, avoid pronouns referring backward. Most web writing assumes sequential reading. Retrieval systems don’t read sequentially, and content structured for humans alone loses citations quietly.
Do AI crawlers need different technical permissions than Googlebot?
Yes, and blocking them accidentally is common. Robots.txt files written years ago often exclude crawlers now feeding retrieval systems: GPTBot, ClaudeBot, PerplexityBot each identify distinctly. Businesses occasionally discover they’ve been invisible to language models for eighteen months because of three lines nobody revisited.