The shift from blue links to agentic responses

For two decades, digital visibility was a game of manipulating Google's index. Brands optimized for keywords and backlinks to ensure they appeared in the top three blue links. This era is ending. As users move toward OpenAI's SearchGPT, Perplexity, and Google's own Search Generative Experience (SGE), the destination is no longer a website—it is an answer. In this new world, if an AI agent does not cite a brand, that brand effectively ceases to exist for a growing segment of the market.

Cited is a Canadian-based agency that has emerged to solve this specific visibility crisis. They specialize in Generative Engine Optimization (GEO), a discipline that treats large language models (LLMs) as the primary searchers. Instead of optimizing for crawlers, Cited optimizes for the latent space of models and the Retrieval-Augmented Generation (RAG) processes that modern agents use to ground their answers in fact.

Optimizing for the latent space

Unlike traditional SEO, which focuses on domain authority and technical site health, GEO requires a deeper understanding of how models synthesize information. Cited focuses on semantic density and citation authority. Their work involves ensuring that a brand's information is presented in formats and contexts that are highly "retrievable" by agents. This often means auditing how a company is represented in common training datasets and ensuring that web-based content is structured to be the most relevant "chunk" of data when an agent performs a vector search.

This approach recognizes that agents are the new gatekeepers. An agent like a customized GPT or a specialized research tool does not browse the web like a human; it digests and summarizes. Cited’s role is to ensure that the summary includes their clients. This involves a mix of strategic content placement, technical data structuring, and semantic analysis to match the patterns that models like Claude, GPT-4, and Llama are trained to prioritize.

Market position and competition

Cited is operating in an early-stage market. Most digital marketing firms are still focused on legacy SEO tactics, creating an opening for specialists who speak the language of embeddings and RAG. While traditional agencies might see GEO as a subset of their existing offerings, Cited treats it as a distinct, standalone requirement for the AI era.

Based in Canada, the firm is part of a small but growing cohort of "agent-first" service providers. Their competition currently includes a handful of boutique GEO firms and the internal growth teams of large enterprises that are beginning to see their referral traffic drop. The challenge for Cited is the "black box" nature of generative models. Unlike Google, which occasionally provides documentation or transparency reports, LLM providers are less explicit about their retrieval algorithms. Cited must rely on empirical testing and a deep understanding of model behavior to provide results. As agents become the primary way we interface with the internet, the ability to be "Cited" by these agents becomes a fundamental business requirement.