Cogya has launched an enterprise AI platform built around the marketing ROI methodology developed by Pablo Turletti, founder and CEO of ROI MONITOR. The platform is designed to turn a methodology refined over 15 years into software that can analyze marketing, business and financial data and help organizations evaluate investment decisions.

The Miami-based AI development and strategy firm developed the platform for ROI MONITOR, positioning the project as an example of how specialist business expertise can be translated into scalable AI systems.

Rather than building a general-purpose chatbot or analytics dashboard, Cogya said its approach focuses on capturing how a domain expert makes decisions and encoding that logic into an AI workflow.

The launch comes as enterprises increasingly look beyond generative AI assistants toward systems that can apply proprietary business knowledge to specific operational problems. For marketing organizations, that shift is particularly relevant as finance teams demand clearer connections between marketing expenditure and revenue outcomes.

Turning Marketing Expertise Into Software

ROI MONITOR was founded by Turletti, who has spent more than 15 years developing a causation-based approach to marketing ROI. The methodology is intended to connect marketing activity with business and financial outcomes instead of relying primarily on metrics such as impressions, clicks or engagement.

According to Cogya, the company mapped the decision-making processes underlying the methodology and converted them into AI-enabled workflows.

The resulting platform brings marketing, business and financial inputs into a common analytical layer. It can create attribution models by product or service category and market, while supporting both pre-investment planning and post-investment evaluation.

For marketing and finance teams, the distinction is important. Many marketing analytics systems are designed primarily to report what happened after campaigns run. ROI MONITOR is intended to address the decision before investment as well as the evaluation afterward.

The platform can estimate forecast ROI, breakeven requirements, marginal sales and opportunity costs, according to the companies. After an initiative is completed, users can evaluate actual ROI and examine factors that contributed to the result.

Cogya has not disclosed independent benchmark results demonstrating the platform's accuracy against established marketing-mix modeling, attribution or financial-analysis approaches.

A Different Approach to Enterprise AI

Cogya's development model centers on its proprietary AI Canvas methodology. The company says its teams work with subject-matter experts to document decision processes and then design AI systems capable of reproducing those processes at scale.

That approach addresses one of the more difficult problems in enterprise AI: valuable organizational knowledge often exists as informal processes, spreadsheets, judgment calls and institutional experience rather than structured software.

Generic AI tools can access enterprise documents and answer questions about them, but that does not necessarily mean they understand how an organization makes investment decisions.

Encoding a methodology requires identifying the variables, relationships, assumptions and decision rules behind it.

In the ROI MONITOR project, that means translating a marketing ROI framework into an analytical system capable of considering multiple business and financial inputs simultaneously.

Cogya says it has applied the same general development approach to projects across marketing technology, engineering, hospitality, luxury distribution and the public sector. The company also develops Cogxera, its multi-agent AI operating platform.

Marketing ROI Remains a Measurement Challenge

The launch addresses a longstanding issue for chief marketing officers: demonstrating the economic contribution of marketing activity.

Digital marketing has produced an abundance of measurable interactions, but more data does not automatically establish causality. A click, impression or conversion may be associated with a campaign without proving that the campaign generated the underlying business outcome.

This is one reason marketing measurement remains closely connected to finance. Organizations need to understand incremental sales, customer acquisition economics, profitability and the opportunity cost of allocating resources to one channel rather than another.

ROI MONITOR's methodology is designed around this problem.

Its pre-investment component could allow marketing and finance leaders to compare potential scenarios before spending takes place. Its post-investment component is intended to assess actual economic performance after execution.

That creates a more continuous measurement cycle than a reporting system used solely at the end of a campaign.

Market Landscape

The marketing analytics market includes attribution platforms, marketing-mix modeling providers, customer data platforms, business-intelligence software and increasingly AI-powered analytics systems.

Large technology vendors such as Google, Salesforce and Adobe provide increasingly sophisticated analytics and measurement capabilities, while specialist vendors focus on attribution, incrementality and marketing effectiveness.

Cogya's approach is narrower: rather than offering another general-purpose analytics environment, it is attempting to operationalize a particular expert methodology.

That specialization can provide a clearer decision framework but also creates a dependency on the quality and applicability of the underlying methodology.

The competitive question will ultimately be whether organizations view expert-led AI systems as more useful for high-value decisions than conventional analytics tools combined with internal expertise.

Why Proprietary Knowledge Is Becoming an AI Asset

The broader implication of Cogya's platform extends beyond marketing.

Enterprises often have proprietary methods for pricing, engineering analysis, procurement, customer segmentation, risk assessment or operational planning. Historically, those methods may have depended on a small group of experienced employees or consultants.

AI provides a potential mechanism for formalizing that knowledge.

The challenge is preserving context. A methodology cannot necessarily be converted into an AI system simply by uploading documents. Decision quality may depend on implicit assumptions, exceptions and relationships between variables that are not clearly documented.

Cogya's model attempts to address that issue by working directly with subject-matter experts to map decision logic before developing the system.

If successful, that approach could become a broader enterprise AI development pattern: capturing specialized knowledge, embedding it into software and making it available across an organization.

Strategic Outlook

The ROI MONITOR platform arrives as marketing organizations face increasing pressure to connect spending with measurable commercial outcomes.

Its most important test will be whether its causal methodology can produce reliable recommendations when applied to different industries, markets and data environments.

Data quality will be a major factor. Marketing performance is affected by pricing, distribution, seasonality, competition, product availability and broader economic conditions. An AI system must distinguish those influences from the impact of marketing activity if its ROI calculations are to inform major investment decisions.

There is also a governance issue. AI-generated financial recommendations should remain explainable enough for marketing and finance leaders to understand the assumptions behind them.

Cogya's launch nevertheless highlights a significant direction in enterprise AI: the opportunity is shifting from generic assistance toward software that incorporates specialized institutional knowledge.

For companies with mature proprietary methodologies, the strategic question may increasingly be whether that expertise should remain dependent on individual specialists or become part of an AI-enabled operating system.

Top Insights

• Cogya launched an enterprise AI platform developed for ROI MONITOR's marketing ROI methodology.
• The methodology was developed by Pablo Turletti over more than 15 years.
• The platform combines marketing, business and financial inputs for pre- and post-investment analysis.
• Its stated use cases include forecast ROI, breakeven analysis, marginal sales, opportunity cost and actual ROI evaluation.
• Cogya's broader strategy focuses on converting domain-expert decision logic into specialized AI systems.
• Independent performance benchmarks for the platform have not been published.

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