Get your brand into AI recommendations.
Get your brand suggested by AI
Our full-service GEO program combines earned media authority, technical optimization, content reformation, and continuous monitoring to make ChatGPT, Claude, Perplexity, and Gemini cite your brand by name.
Trusted by global brands
The Problem
Your Google rank is not good enough anymore.
Ranking on Google and being recommended by AI are two completely different things. We’ve seen it first hand: a brand can hold first page positions for every keyword in its category and still be invisible to the 900+ million people who use ChatGPT every week.
The reason is simple: while AI models certainly consider search engine rankings, they don’t just mirror Google’s top ten results. They evaluate what trusted third-party sources say about a brand before making a recommendation.
If your third-party evidence is thin, inconsistent, or difficult for AI to extract, you will not be recommended, even if you dominate traditional search.
A homepage claim is still a claim. What AI needs is corroboration: distributed evidence across multiple independent sources that a brand is what it says it is.
Most SEO agencies treat GEO as a technical add-on — schema markup, structured data, maybe an llms.txt file. That’s necessary, but it addresses only one of six vectors that drive AI recommendations. The real driver is authority, and authority has to be earned, not coded.
The Holistic Approach
Generative Engine Optimization is not one tactic. It’s a system.
GEO focuses on making a brand discoverable, understood, and recommended by AI platforms. It requires coordinated execution across six vectors — because AI models cross-reference multiple signal types before making a recommendation.
A brand with strong content but no reviews will not get recommended consistently. A brand with excellent reviews but no editorial coverage will be outperformed by a competitor that has both.
AI systems compress uncertainty when they can find the same positioning confirmed across multiple independent sources. When that corroboration exists, recommendation confidence rises. When it doesn’t, the model hedges or defaults to a competitor.
The 6 GEO Vectors
In-house Channel Optimization
Make everything you own machine-retrievable and AI-optimized
Specialized GEO Content
Create authority assets designed to be extracted and cited
Review Stimulation
Generate the review signals AI uses to evaluate credibility
Social Chatter
Build presence in the communities AI models reference
Targeted Paid PR
Amplify milestones across distribution networks AI indexes
Organic PR
Earn coverage in the publications AI models train on and cite
The 6 Vectors: Our Services in Detail
In-house Channel Optimization
Make everything you own AI-readable.
Even strong trust proof fails when it’s hard for AI to parse. Key proof often sits inside expandable components, disconnected case study pages, or visual badges with no textual equivalent. Models are more likely to use evidence that is visible in crawlable text with clear claim-to-proof structure.
We audit and optimize every channel a client controls — from website structured data and llms.txt files to Google Business Profile, Bing Places, Crunchbase, Wikipedia, Wikidata, and 40+ industry directories. The goal is complete entity consistency: every platform tells the same story about the brand, in a format AI can parse and cross-reference.
Deliverables:
- Full website GEO audit (structured data, schema, AI crawlability, extractability scoring)
- llms.txt file creation and deployment
- Entity and knowledge graph optimization (Wikipedia, Wikidata, Crunchbase)
- Directory audit and consistency optimization across 40+ platforms
- Google Business Profile and Bing Places optimization – Robots.txt configuration for AI crawlers (GPTBot, ClaudeBot, PerplexityBot)
- On-site extractability improvements (claim-to-proof structure, crawlable text formatting)
Specialized GEO Content
Content built to be cited, not just read.
Most content is written for humans and optimized for Google. GEO content is different. It’s engineered to be extracted, summarized, and cited by AI models.
AI systems perform sub-document processing, pulling specific snippets and tokens from pages rather than retrieving whole documents. The system isn’t sending users to a page — it’s pulling information from the page into its own answer. Content needs to be structured for extraction, not just for reading.
We also consider how AI models process recommendation queries. When a user asks “which provider is best for me?”, the model internally works through several stages: Discover (“what are the best X?”), Compare (“X vs Y”), Validate (“is X any good?”), and Choose (“which X should I pick for Y use case?”). Each stage requires a different type of content asset.
We create authority assets — research reports, industry guides, comparison content, decision guides, and data-driven articles — structured with clear claims, definitive language, entity-rich formatting, and high factual density.
Deliverables:
- AI-optimized authority articles and guides – e.g. comparison content
- Decision guides by segment and use case
- Proof pages: reviews, outcomes, methodology, FAQs
- FAQ content with FAQPage schema markup
- Research reports and original data studies
- Content reformation of existing assets for AI extractability
Review Stimulation
The trust layer AI can’t ignore.
When ChatGPT recommends a local business, it pulls from review platforms — Google, Yelp, BBB, G2, Trustpilot, and industry-specific sites like Super Lawyers or Healthgrades. Review volume, recency, and sentiment directly influence whether AI models include a brand in recommendations.
From a marketing perspective, reviews are not just conversion assets anymore. They are part of a brand’s recommendation trust graph. Every review on every platform adds another data point that AI systems can use to validate a business. Over time, these mentions compound — the model encounters the brand in enough independent contexts that recommending it becomes a low-risk output.
We design and implement ethical, white-hat review generation systems that consistently produce fresh, detailed reviews across the platforms that matter for each client’s industry and AI visibility.
Deliverables:
- Review platform audit (which platforms should you be on)
- Review generation funnel design and implementation: creative strategies, customer follow-up sequences, and touchpoint optimization
- Review response management and sentiment optimization
- Cross-platform review consistency monitoring
Social Chatter
Be part of the conversations AI is learning from.
Reddit is the #1 most-cited domain in Google’s AI Overviews. YouTube ranks in the top 3. Forums, discussion threads, and social media conversations are primary training data for every major LLM.
Reviews and user-generated content function as corroboration layers. When external feedback repeatedly validates a brand’s core claims, recommendation confidence rises. When proof is sparse, generic, or siloed on one platform, models have less reliable support. A homepage claim is still a claim. A distributed pattern of consistent public discussion is closer to evidence.
We build genuine presence in the communities that matter — Reddit, X, LinkedIn, niche forums, and Quora. This is not astroturfing. It’s value-driven participation: AMAs, thought leadership posts, community contributions, and engagement strategies that spark real conversations about brands and their expertise.
Deliverables:
- Reddit strategy and community engagement
- X/Twitter thought leadership campaigns
- LinkedIn content strategy for founder and team profiles
- Niche forum presence building
- Community monitoring and sentiment tracking
Targeted Paid Releases
Amplify milestones where AI is watching.
Not every milestone warrants a full organic PR campaign, but every significant achievement can generate AI-visible signals. Strategic press releases distributed through premium networks create structured, timestamped content that AI models encounter during both real-time retrieval and training data ingestion.
Each release is structured for AI extraction: clear claims, quotable statements, entity-rich formatting, and distribution to outlets that AI platforms index. This is particularly effective for creating fresh validation signals — our research indicates that AI models appear to value recency, meaning recent coverage carries more recommendation weight than older mentions.
Deliverables:
- Strategic press release drafting optimized for AI extraction
- Premium distribution across newswire networks
- Sponsored articles in leading media outlets
- Post-release citation monitoring across AI platforms
Earned PR
The authority signal AI trusts most.
AI models like ChatGPT, Claude, and Perplexity determine brand credibility by analyzing what independent, authoritative sources say about a brand. The most-cited domains in ChatGPT responses include Reddit, Wikipedia, Amazon, Forbes, and Business Insider. The pattern is clear: editorial and user-generated content from trusted sources dominates AI citations.
We’ve spent 8+ years building relationships with journalists, editors, and publishers across hundreds of outlets. We don’t send mass press releases. We secure genuine editorial coverage — feature articles, expert interviews, product inclusions in roundups, podcast appearances — in the publications AI models actually reference.
What matters is not just any mention, but context-matched coverage. Generic global coverage says a brand exists. Contextual coverage — tied to the right geography, category, and buyer intent — says a brand belongs in a specific decision set. We’ve seen firsthand how even a single inclusion in a region-specific listicle by reputable independent media can make the difference between no recommendation and a top recommendation.
Deliverables:
- Feature articles and brand mentions in top-tier and industry-specific publications
- Expert source placements and journalist relationship management
- Podcast booking and interview coordination
- Listicle and roundup inclusion campaigns (contextually matched to geography and category)
- Publication-specific pitching strategies aligned with AI citation patterns
How we work
From invisible to recommended in four phases.
Step 01
Discovery
We analyze what ChatGPT, Gemini, Claude and other AI models think about both your brand and your competitors across hundreds of unique prompts. We map out your entire digital footprint.
Completed by: week 1
Step 02
Strategy
We identify vectors that require improvement – whether it’s brand mentions, user content, or in-house channels. We define milestones, target publications, platforms, and citation goals.
Completed by: week 2
Step 03
Execution
Simultaneous execution across all relevant vectors. We build LLM-optimized foundations, craft content, secure organic media placements, and develop your social presence.
Starting from: week 2
Step 04
Iteration
AI visibility is not a one-time project. We continuously track your AI citations, monitor improvements and competition, and identify areas that require immediate attention.
Starting from: week 4
Get Started
Find out if your brand is AI-ready.
Free Audit
Get a free AI visibility audit assessing your content, technical structures, and more. See exactly where you stand in under 48 hours.
No commitment. No retainer. Just data.
What it includes:
- AI citability & visibility score
- Technical foundations & data review
- Content & EEAT audit
- Optimization score for specific platforms
- Action Plan
Transparency
GEO in 2026: an honest assessment
The potential of generative engine optimization for lead generation is hard to overstate. All signs point towards LLM usage for purchase decisions increasing exponentially over the coming years.
That said, GEO difficulty varies enormously. For businesses in smaller niches, such as local services, specialized B2B, regional markets, meaningful results can come within weeks to months.
For a new entrant trying to break into a highly competitive global category from zero, like credit cards, it’s a multi-year effort and requires considerable marketing firepower. We’d rather be upfront about that than overpromise.
Three factors determine where you fall on this spectrum:
1. How competitive is your industry?
In categories where established players have hundreds of editorial mentions and years of review history, competing from scratch takes significant time.
The quick solution: niche down and specialize. A new fintech startup won’t get recommended as “the best banking app” overnight — but it can become the recommended solution for “the best banking app for freelancers in Germany.” GEO work should focus on owning a specialization first, then expanding.
2. What is your current digital footprint?
Every existing media mention, review, and directory listing is an authority asset AI can reference. Brands with an established footprint see results faster. Brands starting from zero need to build that foundation first — achievable, but it requires patience.
Most businesses fall somewhere in between, where GEO delivers the fastest ROI: optimizing what exists while filling critical gaps first.
3. How strong is your actual product or service?
This is the factor agencies rarely mention. Building authority is dramatically easier when a business genuinely delivers value. Real satisfaction leads to organic reviews. Genuine expertise attracts media interest.
A truly differentiated offering gives journalists a reason to cover it. We can amplify and accelerate what’s there.
Who this is for
PolyGrowth GEO was built for
Startups
New brands need to build AI visibility from scratch. We create the authority foundation — editorial coverage, reviews, content — that puts startups on the map of AI models.
B2B services
9 in 10 B2B buyers already use AI to research vendors. We ensure your brand appears when decision-makers ask AI for recommendations in your category.
Local professionals
Lawyers, consultants, medical practices, financial advisors — we build the review presence and local editorial coverage that drives those recommendations.
SaaS companies
AI recommends software based on what third-party sources say — not what your landing page claims. We build the distributed validation that gets picked up by AI.
Real Estate firms
Buyers & sellers increasingly ask AI for RE agency recommendations. We build the local authority signals that put your firm in those answers.
Healthcare brands
Patients research providers through AI before booking. We build the trust signals that make AI confident enough to recommend your practice.
How we think
GEO is new. We treat it that way.
GEO as a discipline is barely two years old. Platforms change constantly. No one has all the answers yet — including us.
What we do have is an approach that has proven durable and replicable: earning real authority through independent sources aligns with how AI models fundamentally evaluate trust. Regardless of how specific platform mechanics evolve, the principle that AI recommends brands it can verify through third-party evidence is unlikely to change.
That said, we don’t treat our approach as settled. We continuously test across platforms, track how citation patterns shift with model updates, and adapt based on what we observe. We publish our findings openly on our blog — including when results surprise us and when the landscape shifts in ways nobody predicted.
The agencies that will lead GEO long-term are not the ones claiming to have it all figured out. They’re the ones still learning.
Case Studies
What happens when AI trusts your brand.
Case Study 01
From invisible to top recommendation.
The Context:
This B2B SaaS client occupied top Google ranks but still wasn’t recommended by ChatGPT, Gemini, and Co.
The Outcome:
Less than a year later, it is now being recommended and cited across all major AI tools for its most crucial prompts.
Thanks to PolyGrowth, our local business is ranked #1 on Google for our most important keywords and has been recommended as the best option on ChatGPT for 2+ years now.
We really enjoyed working with the PolyGrowth team. The results were exactly as promised and we look forward to our next project with them.
"We highly recommend Simon and the PolyGrowth team. They were extremely easy to communicate with and provide an exceptional service with great turnaround time. We will continue to use their services long term and would encourage anyone else to do the same."
FAQs
About PolyGrowth's GEO service
GEO is the practice of optimizing a brand to be recommended by AI platforms like ChatGPT, Claude, Perplexity, and Google’s AI Overviews. It combines earned media, technical optimization, content strategy, review management, and entity building into a coordinated system. Unlike SEO, which focuses on ranking in a list of search results, GEO focuses on being cited and recommended inside AI-generated answers.
SEO and GEO share some foundations (content quality, structured data) but diverge significantly. SEO focuses on Google’s ranking algorithm: keywords, backlinks, page speed. GEO focuses on AI citation: entity presence, distributed third-party validation, extractable content, and review signals. A strong Google ranking helps discovery, but distributed corroboration across independent sources is what drives recommendation confidence.
AI models determine brand authority by analyzing what trusted third-party sources say. The most-cited sources in AI responses are editorial publications and curated lists. PR is the discipline that earns those placements. Without it, a GEO strategy is missing its most powerful lever. In our research, the brands recommended most consistently by ChatGPT were those easiest to corroborate through independent editorial mentions.
ChatGPT, Claude, Perplexity, Google AI Overviews / AI Mode, Gemini, Copilot, and Grok. Each platform has different data sources and citation behaviors. For example, ChatGPT’s shopping widget is powered by Google Shopping data, while its local recommendations pull heavily from Foursquare and Bing web results. We optimize for all of them, accounting for platform-specific mechanics.
We track citation frequency, recommendation positioning, and sentiment across all major AI platforms using prompt-by-prompt monitoring. Monthly reports include competitive benchmarking, trend analysis, and gap identification. We measure what matters: how often AI recommends the brand, in what context, and how that changes over time.
Real-time platforms (Perplexity, ChatGPT Browse) can reflect changes within weeks. Training-data-dependent platforms take longer — typically 60–90 days for initial citations. Category leadership usually takes 6–12 months of sustained effort. The timeline also depends on the starting point: a brand with existing editorial coverage and reviews will see results faster than one starting from scratch.
Our GEO program includes all six service vectors. For companies that already handle some vectors in-house, we can tailor the scope. We also offer standalone PR services for companies that handle GEO internally but need earned media support — details on our PR services page.
Most GEO agencies are SEO agencies that added GEO as a service. Their authority-building toolkit is limited to structured data, content hubs, and directory listings. We come from 8+ years of earned media — securing real editorial coverage in real publications. That capability is our core, and it addresses the signal AI models weight most heavily: independent third-party validation. No other GEO agency has this background.