Alex Dees is the co-founder and CEO of Meridian, a pioneering AI visibility platform based in New York City. Under his leadership, Meridian has emerged as a critical tool for brands navigating the transition from traditional search engines to AI-driven conversational interfaces like ChatGPT, Perplexity, and Google Gemini.

The shift in consumer behavior is undeniable. As users increasingly turn to AI assistants to find, evaluate, and purchase products, the traditional SEO playbook—once built on backlinks and keyword density—is being rendered obsolete. Alex Dees recognized this gap early, pivoting from a successful career in embedded fintech to build the infrastructure for what is now known as Generative Engine Optimization (GEO).

Why the Traditional Search Model is Breaking Down

For over two decades, the relationship between brands and consumers was mediated by "ten blue links." SEO teams focused on moving their website from page two to page one, optimizing for crawlers that indexed the web to provide a directory of destinations. However, the rise of Large Language Models (LLMs) has collapsed this journey. Instead of a list of websites, users now receive a single, synthesized answer.

In this new reality, being "on the first page" matters less than being the "cited source" within an AI's response. Research indicates that a significant percentage of searches are now moving toward these AI-native experiences. When an AI assistant recommends a product or explains a concept, it acts as a gatekeeper with more influence than any traditional search ranking. If a brand is not mentioned in the AI's response, or worse, if the AI provides incorrect or negative information, the brand effectively ceases to exist in that user's journey.

The Professional Journey of Alex Dees

Alex Dees did not start his career in AI, but his background in high-growth startups provided the perfect foundation for founding Meridian. Before co-founding the company, Dees served as the Head of Business Development for an embedded fintech company. During his tenure, he was responsible for scaling the organization from its pre-seed stage through its Series B funding round.

This experience was pivotal. Managing the entire customer journey—from initial sales to solutions engineering—gave Dees a "front-row seat" to the complexities of digital commerce and agentic behavior. He observed how AI was beginning to make decisions on behalf of users, particularly in the financial and purchasing sectors. Dees realized that while the technology to generate answers was advancing rapidly, the tools for brands to monitor and influence those answers were non-existent.

This realization led to the formation of Meridian. Dees assembled a lean, highly technical team focused on a single mission: providing visibility into the "black box" of AI recommendations.

What is Meridian and How Does It Function?

Meridian is often described as the first true "visibility engine" for the AI era. Unlike traditional SEO tools like Ahrefs or SEMrush, which monitor Google’s SERP (Search Engine Results Page), Meridian monitors the outputs of various LLMs. It provides marketing and SEO teams with a clear picture of how their brand, products, and services are interpreted and recommended by artificial intelligence.

AI Visibility Tracking and Sentiment Analysis

The core of the Meridian platform is its ability to track brand mentions, sentiment, and ranking positions across a multitude of AI assistants. In our testing of the platform, the granularity of data is what sets it apart. Meridian doesn't just tell you if you were mentioned; it analyzes the context. Is the AI recommending your product as a top-tier option, or is it mentioning you as a budget alternative?

By running hundreds of simulated prompts across models like GPT-4o, Claude 3.5, and Gemini Pro, Meridian builds a statistical map of a brand’s "Share of Voice" in the generative space. This allows companies to see trends over time, identifying whether a recent product launch or PR campaign has successfully penetrated the training data or retrieval-augmented generation (RAG) pipelines of these models.

Deep Citation and Source Analysis

One of the most innovative features Alex Dees and his team implemented is the Source Analysis tool. AI models generally pull information from two places: their underlying training data and real-time web searches. Meridian identifies exactly which websites, articles, or reviews the AI is citing when it generates an answer.

For a marketing team, this is transformative data. If an AI consistently cites a specific competitor's blog post when asked about "the best enterprise CRM," Meridian highlights that gap. It allows brands to identify "missing content"—the specific pieces of authority and information they need to publish or update to become a preferred source for the AI.

Actionable Workflows for Generative Engine Optimization

Dees has been vocal about the fact that data without action is useless. Meridian includes "Action Workflows" that prioritize specific opportunities. For example, the platform might identify that a brand’s technical documentation is being misinterpreted by an AI crawler due to poor schema markup. The workflow would then provide the exact technical fix required to improve the AI's understanding of that product.

These workflows extend to off-site opportunities as well. Meridian can identify third-party authoritative sites (like Reddit, industry forums, or specialized review sites) that the AI frequently cites. By improving their presence on these external channels, brands can indirectly improve their visibility within AI answers.

The Rise of Generative Engine Optimization (GEO)

Under the guidance of Alex Dees, Meridian is leading the charge in a new discipline called Generative Engine Optimization (GEO). While traditional SEO is about keywords, GEO is about "information density" and "authority signals."

AI models are trained to find the most relevant, truthful, and authoritative answer. To win in this environment, brands must shift their strategy. In our internal analysis of successful GEO campaigns, we’ve observed that "fluff" content—the long-winded, 2,000-word blog posts designed to rank for a keyword—actually performs poorly in AI search. AI models prefer dense, fact-rich content that is easy to parse.

The Role of Trust Signals

Alex Dees frequently emphasizes that in the AI-native era, trust signals like reviews and domain credibility are weighted differently. AI assistants are risk-averse; they don't want to provide a recommendation that leads to a poor user experience. Consequently, they look for consensus across multiple authoritative sources.

Meridian helps brands monitor this consensus. If there is a "hallucination" where an AI claims a product has a feature it doesn't, or lacks a feature it does, Meridian’s tools allow teams to trace the source of that misinformation and correct it at the root.

Case Study: From Zero Visibility to Market Leadership

The impact of Meridian’s approach is best illustrated through its early adopters. One notable success story involves Christian & Timbers, an elite executive search firm. Before using Meridian, the firm had virtually zero visibility for relevant recruiting queries within AI chat interfaces.

By using Meridian to identify gaps in their content strategy and third-party citation presence, they were able to systematically address weaknesses in their on-site positioning and off-site authority signals. Within eight weeks, the firm achieved a 60% mention rate for their target queries. They weren't just "on the list"; they were being recommended by AI assistants with genuine confidence, often alongside much larger, established competitors.

Challenges in the AI Visibility Sector

Despite the rapid growth, Alex Dees acknowledges that the sector faces significant challenges. One of the primary hurdles is the inconsistency of AI answers. Because LLMs are probabilistic, the same prompt can yield different results at different times.

To solve this, Dees and his engineering team built repeatable test sets with rigorous scoring methodologies. By running a prompt hundreds of times and averaging the results, Meridian provides a reliable "Visibility Score" that filters out the noise of model temperature and randomness.

Another challenge is attribution. Unlike traditional search, where a user clicks a link and generates a trackable session, AI interactions often happen within the chat interface itself. Dees has focused Meridian’s roadmap on building "leading indicators" and proxy metrics that correlate with revenue, helping marketers prove the ROI of their AI optimization efforts.

The Future of Brand Discovery According to Alex Dees

Alex Dees views the current state of AI search as just the beginning. As AI agents move from "answering questions" to "executing tasks"—a concept known as agentic commerce—the stakes for visibility will only increase. Imagine an AI agent that is authorized to book a flight, buy a pair of shoes, or hire a contractor on behalf of a user. In that scenario, the AI isn't just a search engine; it is the customer.

Dees’ vision for Meridian is to become the standard platform for this new era. Future goals for the company include:

  • Increased Automation: Building AI-generated content briefs and technical fixes that teams can execute with a single click.
  • Deep Attribution: Connecting AI visibility improvements directly to the sales pipeline with greater precision.
  • Cross-Platform Integration: Expanding beyond text-based LLMs to include multimodal AI assistants that analyze images and video.

Summary: Preparing for the Post-SEO World

The emergence of Alex Dees and Meridian marks a turning point in digital marketing. We are moving away from an era of "gaming the algorithm" and toward an era of "proving authority to intelligence."

For brands, the message is clear: the strategies that worked in 2020 will not work in 2025. Visibility is no longer guaranteed by a high marketing budget or a surplus of backlinks. Instead, it is earned through data-driven optimization, clear information architecture, and a deep understanding of how AI interprets the world. As Alex Dees continues to scale Meridian, he is providing the map and the compass for brands to navigate this unfamiliar, AI-driven landscape.

Frequently Asked Questions

What exactly is AI Visibility?

AI Visibility refers to how frequently and accurately a brand or product is mentioned, recommended, and cited by AI assistants like ChatGPT, Claude, and Gemini. It is the core metric for measuring success in Generative Engine Optimization (GEO).

How does Meridian differ from traditional SEO tools?

Traditional SEO tools track rankings on search engines like Google. Meridian tracks "mentions" and "citations" across multiple LLMs. It focuses on the content of AI-generated answers rather than just the order of search results.

Who is Alex Dees?

Alex Dees is a tech entrepreneur and the CEO of Meridian. He has a background in scaling fintech startups and is a leading voice in the shift toward AI-native brand discovery and marketing.

Can Meridian help fix incorrect information in ChatGPT?

Yes. Meridian’s Source Analysis tool helps identify the specific websites or documents that an AI is using as a source for its answers. By correcting the information at the source, brands can influence and correct the AI’s future outputs.

What is Generative Engine Optimization (GEO)?

GEO is the practice of optimizing digital content so that it is more likely to be retrieved and positively recommended by generative AI models. It involves improving information density, technical schema, and authoritative citations.