Researcher Carlos Ricardo Jurado Peralta proposes a new approach to AI search visibility, challenging how large language models discover, evaluate, and recommend businesses online. His findings have led to the development of QCSM-Webcert and several AI-powered business platforms.
TECHNOLOGY & INNOVATION — November 11, 2026. As artificial intelligence reshapes how businesses are discovered online, entrepreneur and researcher Carlos Ricardo Jurado Peralta believes he has identified a fundamental weakness in the way generative AI systems retrieve and cite information from corporate websites.
His investigation began with a practical business problem: finding reliable international financing providers for clients seeking long-term capital.
What started as a routine search using ChatGPT eventually developed into a ten-week research project, a published scientific paper, and a growing portfolio of technology ventures.
How a Search for International Financing Exposed a Potential AI Visibility Problem
While returning to his professional activities as an independent placement agent, Jurado Peralta was researching international financing opportunities for clients seeking long-term loans.
He used ChatGPT to identify providers across several financial sectors, including family offices, private credit firms, and private banking institutions.
Despite the large number of financial organizations operating internationally, his search reportedly produced only 26 results, including two duplicates.
The limited response raised an important question: Why would a generative AI system return such a narrow selection when thousands of potential providers might exist?
The results did not necessarily represent the most suitable financial institutions for his clients.
Rather than accepting the output, Jurado Peralta began investigating the factors that might prevent relevant companies from appearing in AI-generated recommendations.
The research process lasted approximately ten weeks.
The AI Search Visibility Problem: Why Some Websites May Remain Invisible to Large Language Models
Jurado Peralta’s investigation focused on a growing challenge in digital marketing and information retrieval: the visibility of corporate websites in AI-powered search systems.
Platforms such as ChatGPT, Google Gemini, Perplexity, and Claude increasingly influence how users research products, compare services, and identify potential business partners.
However, appearing prominently in conventional search engines does not automatically guarantee that a company will be mentioned or cited in an AI-generated response.
Different AI platforms use different combinations of training data, retrieval systems, search indexes, and ranking mechanisms.
Jurado Peralta argues that weaknesses in website structure and machine-readable information can contribute to the exclusion of otherwise relevant businesses from AI-generated results.
His proposed approach emphasizes the technical architecture of websites rather than relying exclusively on traditional indicators of online popularity.
The QCSM Paradox: Research Examines 150 Corporate Websites
The investigation resulted in a research paper titled The Paradox of Digital Invisibility: Quantifying the Impact of Algorithmic Blindness in Corporate Data (N=150 Analysis).
Published on Zenodo on December 30, 2025, the study examines 150 corporate websites across ten industries.
The paper explores whether structural website characteristics, including canonical tags and structured data markup, may be stronger predictors of visibility in generative AI systems than conventional brand popularity.
The study reports an ordinary least squares regression model with an R² value of 91.82%.
However, it also identifies severe multicollinearity, with variance inflation factors exceeding 42, creating important limitations for interpreting the statistical relationships.
Jurado Peralta describes this problem as the “QCSM Paradox,” suggesting that technically inadequate website architecture may prevent valuable businesses from being properly represented in AI-generated information.
The research proposes a Quality Certification Scoring Model, or QCSM, designed to evaluate technical factors associated with corporate digital visibility.
Although the paper presents a potentially useful framework, its findings require further independent validation before broader conclusions can be established.
From Research to QCSM-Webcert: Building Tools for AI Search Optimization
The research inspired the development of QCSM-Webcert, a technology platform focused on website architecture, structured data, and AI-oriented digital visibility.
The service promotes technical audits intended to identify weaknesses that may affect how automated systems interpret corporate information.
Its approach includes examining website structure and implementing machine-readable information through technologies such as JSON-LD.
These methods are relevant to search engine optimization and structured information retrieval, although their ability to secure specific recommendations from generative AI platforms has not been independently established.
Jurado Peralta sees the project as part of a broader shift from conventional search engine optimization toward preparing business information for increasingly automated digital environments.
RevenueBrokers and MediPlay Expand the AI-Powered Business Ecosystem
The entrepreneur’s development activities subsequently expanded into additional technology ventures.
RevenueBrokers focuses on business-to-business commercial infrastructure, digital platforms, and systems intended to support corporate revenue generation.
Another project, MediPlay, targets healthcare professionals with software designed to integrate medical practice administration, scheduling, billing, and AI-assisted workflows.
Together, these ventures illustrate Jurado Peralta’s interest in building interconnected digital services rather than developing a single standalone product.
He also reports having additional projects under development, particularly in Data-as-a-Service (DaaS), a business model in which data resources and related capabilities are delivered through digital services.
Can AI Reduce Software Development Costs and Timelines?
One of the entrepreneur’s central observations concerns the impact of artificial intelligence on software development.
According to Jurado Peralta, creating a platform such as QCSM-Webcert through conventional development methods could have required at least three years and approximately $2 million in research and development investment, based on Latin American labor costs.
He argues that AI-assisted development tools have substantially accelerated the process of designing software logic, developing algorithms, testing functionality, and bringing products closer to commercial deployment.
These figures represent his own estimates rather than independently audited development costs.
Nevertheless, his experience reflects a broader technological shift in which AI-assisted programming tools can help entrepreneurs prototype applications, automate repetitive tasks, and accelerate certain stages of product development.
The actual savings depend on technical complexity, security requirements, testing standards, and the resources available to each development team.
Why AI Search Optimization Could Matter for Businesses
As AI-generated answers become another way for customers to discover businesses, companies face new questions about how their digital information is organized and presented.
Traditional SEO remains important, but businesses are also examining how structured data, clear corporate information, accessible content, and technical website quality influence automated information retrieval.
Jurado Peralta believes his research could contribute to this emerging field.
He is currently working to validate his findings and expects further results in the coming months.
His long-term objective is to develop systems that help relevant companies become more accurately represented in AI-generated business recommendations.
However, no independent evidence currently establishes that his algorithm can guarantee inclusion, citations, or preferred placement in ChatGPT, Gemini, Claude, or Perplexity.
The Future of AI Entrepreneurship: Technology as an Accelerator, Not a Substitute for Strategy
Beyond the technical research, Jurado Peralta’s experience offers a broader perspective on entrepreneurship in the artificial intelligence era.
He argues that AI should not be treated as a system capable of automatically fulfilling every business ambition.
Instead, he sees it as a powerful development tool that can help entrepreneurs execute well-defined ideas faster, reduce certain operational barriers, and address real market problems.
For founders, the challenge is not simply gaining access to advanced AI platforms. It is identifying a meaningful problem, developing a viable solution, and building an organization capable of sustaining growth.
His experience also highlights a familiar entrepreneurial risk: an innovative product can attract opportunities faster than its business infrastructure is prepared to handle them.
As Jurado Peralta continues validating his research and developing new ventures, his work contributes to the expanding conversation about AI search visibility, digital entrepreneurship, and the commercial applications of generative artificial intelligence.
The central lesson is that artificial intelligence can accelerate the journey, but entrepreneurs still need to know where they want to go.
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Research reference: Carlos Ricardo Jurado Peralta, The Paradox of Digital Invisibility, Zenodo, December 30, 2025. DOI: 10.5281/zenodo.18097499.
Editor’s note: The algorithm’s claimed significance, projected development savings, and potential commercial benefits reflect the researcher’s statements. Independent validation of these claims remains necessary.
