Durham-based startup Majentic builds tools for an Internet increasingly shaped by artificial intelligence. Its platform helps businesses transition from traditional search engine optimization (SEO) to AI engine optimization (AEO), enabling visibility and citations as search moves from humans to machines.
Majentics was founded by Dirk Nicol, who, shortly after completing a decade at IBM, began working for a blockchain computing company where he used early versions of ChatGPT and other LLMs. Quickly understanding the relevance of AI, he used it to help him implement a major go-to-market plan after his team was cut in half.
This process helped him recognize that technology was going to change the future, and he decided he wanted to be part of that change.
“Either I was going to stay in business and go into AI, or I was going to go all out – and I decided to go all out,” Nicol said.
A changing landscape
The first version of what would become Majentics began as AI Transformation, a consulting practice through which Nicol focused on helping small businesses and large enterprise clients understand and adopt artificial intelligence. While training others, Nicol was simultaneously deepening his own expertise.
Eventually, a client, a small e-commerce business, asked for help using AI to improve search engine optimization. This request triggered an awareness at Nicol that went beyond SEO: the way search worked was already evolving, and quickly.
For decades, the Internet was designed around humans. Search engines like Google assumed that a person would type in a few keywords, browse links, and click on websites. The results were largely deterministic, meaning that if two people searched for the same phrase, they would get almost identical results. Modern digital marketing and SEO practices have essentially been built around optimizing these predictable search systems.
But as Nicol recognized early on, AI has disrupted the model. Large language models like ChatGPT are conversational, context-aware, and non-deterministic, producing different answers to the same questions based on wording, prior interactions, model updates, and so on. Instead of returning a list of links, AI systems synthesize the information and provide direct answers.
(With AI) there’s a lot more variability (than traditional search),” Nicol said, “That creates a problem for brands.”
This shift has led to what is known as zero-click search, in which users increasingly get the information they need without ever visiting a website, even though an AI system may have extracted that information. As a result, traffic to websites is down. An objective that naturally emerges for brands wishing to regain visibility and traffic must be cited in the responses generated by AI.
This is the kind of outcome Nicol helps companies optimize with its product.
How Majentics optimizes
The current version of Majentics analyzes a website by ingesting its URL and returning scores in four categories: human conversion, SEO, AI engines, and AI agents. It also provides recommendations and suggestions for quick solutions.
The platform evaluates human-centered marketing and conversion elements such as layout, clarity and calls to action, as well as traditional SEO factors such as content quality, structure and user experience signals. It also evaluates AI engine optimization, providing an AEO readiness score and an example snippet showing how an AI system might describe the site or business in question.
Majentics ultimately generates an AI Agent Readiness Score for a given customer, measuring how ready a site is for agent-driven interactions, including access to structured data and machine readability. Each category is rated on a 100-point scale.
Beyond analyzing individual sites, the platform also examines how a brand appears in AI search results, which competitors are cited and why. It then identifies gaps and suggests actionable fixes, including schema markup, FAQ structures, content organization, and semantic optimization.
Nicol has three pending divisional patent applications related to the startup’s AI readiness scoring system.
Recognition and follow-up
In the short term, Majentics is focused on launching its paid SaaS platform (the current product is a free version) and building stable revenue, primarily by serving marketing agencies and small and medium-sized businesses that are already feeling the effects of declining web traffic and changing search behaviors.
“Agencies will probably be very good immediate customers. They’re under pressure, their SEO business is drying up, so they’re looking for a new business: AEO,” Nicol said. “They might not know how to do it, so (Majentics) could be a great way to create a new product line for them.”
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Start-up: Majentics
Founder: Dirk Nicol
Founded: 2025
Team size: 1
Location: Durham
Website: majentics.com
Funding: bootstrapped
Longer term, Nicol envisions Majentics expanding beyond search and becoming a broader platform designed for machine-centric customer journeys. As AI agents increasingly handle search, purchasing and decision-making on behalf of users, businesses will need new tools to structure content, data and interactions for machines rather than humans.
Nicol expects this shift to reshape marketing teams, workflows and even job roles, creating demand for entirely new ways to manage digital presence.
Since launching the company, Nicol has integrated himself into the North Carolina startup ecosystem. He was accepted into the FCAT fellowship shortly after joining American Underground (he presented last fall in the program demonstration day) and has since participated in several pitch competitions, including Business135 And Converge towards the southwhere he received early validation for his approach with Majentics.