AI-generated answers are now the default for millions of searches. If your content isn’t cited in Google AI Overviews, ChatGPT, or Bing Copilot, your brand is invisible where buying decisions start.
Go Fish’s Generative Engine Optimization services are purpose-built for this shift. We help brands get referenced, cited, and surfaced in AI-driven search by combining:
We don’t guess at what works. Our proprietary tools analyze how AI models choose sources, then we optimize your content to match; page by page, passage by passage.
Your next customer is already seeing AI answers. Are you being cited or left out?
Traditional SEO isn’t enough anymore. With over 58% of U.S. searches ending in zero clicks and Google AI Mode surfacing conversational answers instead of blue links, brands must optimize for AI-first discovery.
Our service combines structured content, technical foundations, and intent-rich strategy to ensure your site appears in AI-generated experiences across search, chatbots, and voice interfaces.
Large Language Models like ChatGPT, Google AI Overviews, and Bing Copilot are changing how people discover brands. If your site isn’t being referenced, summarized, or cited in these AI experiences, you’re invisible.
Our approach focuses on four key areas proven to improve inclusion and visibility across AI-powered search.
We semantically map your entire site to identify how AI systems interpret your authority on key topics.
We analyze and optimize individual pages and passages using the same technology that language models use to power AI generated answers.
Even the best content won’t be included in summaries if it isn’t discoverable. We make sure your content is indexed, structured, and prioritized correctly.
Citation frequency is one of the strongest predictors of inclusion in AI Overviews. Our digital PR team helps your brand show up in the right places.
We use a suite of proprietary tools to help brands improve visibility in AI-generated search experiences, from ChatGPT to Google AI Overviews. These tools allow us to:
Identify content opportunities within AI-generated summaries.
Track performance across emerging AI interfaces
Prioritize high-impact optimizations based on semantic signals.
Semantic Content Audit: Evaluates your entire site to ensure the topics and information most important to your business align with how AI and search engines identify topical experts and authority.
AI Overview Analyzer: Audits your visibility and reference frequency within Google’s AI-generated answers while identifying specific tactics that will help improve your pages inclusion in AI overviews.
Similarity Score Extension: Measures how closely your content matches AI-generated responses, helping you reverse-engineer what’s working.
Barracuda: An AI-powered marketing platform that delivers in-depth page-level analysis, evaluating your content against 14 key factors identified in Google’s own patents as influential to search rankings..
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From high-volume eCommerce to niche B2B, our AI visibility strategies are built to scale across sectors and business models.
Generative engine optimization (GEO) is the process of structuring your content so that it’s eligible to be retrieved, ranked, and summarized by AI systems like Google’s AI Overviews, AI Mode, and ChatGPT. Unlike traditional SEO, which focuses on ranking web pages in the classic “10 blue links,” GEO ensures your content is semantically rich, topically authoritative, and formatted in a way that large language models (LLMs) can understand and surface in AI-generated summaries. This includes aligning with user intent, using structured formats (like FAQs, tables, and lists), and answering long-tail informational queries clearly within content passages.
This approach is informed by several key Google patents and publications. One is US11769017B1, which details how Google retrieves information using neural networks and grounds generative summaries in web-based content. Another is WO2024064249A1, which explains query decomposition and fan-out techniques to improve diverse result retrieval. Additional patents on passage ranking (e.g., US20190372508A1) and user-context-based answer generation also support the idea that Google is optimizing at the passage and entity level, not just by page or keyword.
Query-fanning is a retrieval method used by Google’s AI Mode to handle long, complex, or layered search queries. Instead of treating a user’s input as a single, monolithic query, Google breaks it into multiple sub-queries—each designed to target a distinct aspect or intent embedded in the original question. These sub-queries are run independently to gather a broader and more diverse set of high-quality results. The outputs are then synthesized into a single, coherent AI-generated summary.
This technique is critical for visibility in AI Mode because it allows Google to surface deeper, more nuanced content—even if your page only addresses one part of a complex query. If your content clearly answers sub-topics or related questions using well-structured, semantically relevant passages, it becomes eligible to be retrieved during the fan-out process. This means optimizing for long-tail queries, topical breadth, and structured answers significantly increases your chance of being included in AI-generated responses.
Passage-level optimization refers to the practice of structuring your content so that individual paragraphs or sections can stand alone as semantically relevant answers to user queries. Google’s AI systems (and ChatGPT) now evaluate and retrieve specific passages—not just entire pages—based on their relevance and clarity.
This means each section of your content should include direct, well-formatted answers using clear headers, concise language, and scannable structure (tables, bullet points, and other rich content). Strong passage optimization increases the likelihood that your content will be used in AI-generated summaries and featured responses (higher rank position and brand visibility).
