ZeeQuest Advances Daty.ai with New CDMA Large Language Model Developed by Jasmina Mohorn
The new language layer is designed to turn structured compatibility analysis into clearer, personalized explanations, strengthening the technology behind Daty.ai’s Relationship Intelligence platform.
ZEEQUEST TECHNOLOGIES | OCTOBER 2026
ZeeQuest has reached a new development milestone within Daty.ai. The latest upgrade to the proprietary Compatibility Dimension Mismatch Analysis framework, known as CDMA™, now incorporates a large language model developed by AI expert and business architect Jasmina Mohorn. The test rounds completed so far have been successful.
The development adds a dedicated language layer to the analytical architecture behind Daty.ai. Its purpose is to help translate complex compatibility results into explanations that users can understand, question and apply. The underlying analysis remains structured within CDMA™, while the LLM supports the communication of those results in natural language.
CDMA gains a dedicated language layer
Compatibility Dimension Mismatch Analysis is Daty.ai’s proprietary framework for identifying hidden areas of potential incompatibility across multiple relationship dimensions. These can include communication patterns, values, emotional expectations, timing, life priorities, readiness and personal growth trajectories.
The objective is not to predict certainty or make decisions for users. CDMA™ is designed to surface potential friction that may otherwise remain difficult to see during the early stages of a relationship. This gives users an additional basis for reflection before they make significant emotional decisions.
The new large language model extends that framework by helping convert structured outputs into clear explanations. Instead of presenting only a score or technical result, Daty.ai is being developed to explain which dimensions may be aligned, where mismatches may exist and why those differences could matter in practice.
Analysis and explanation remain separate
The separation between the analytical engine and the language layer is important. CDMA™ provides the compatibility structure. The LLM is being developed to interpret and communicate approved outputs from that structure. It is not intended to invent the underlying compatibility result or replace human judgment.
This approach gives Daty.ai a more credible technical foundation than asking a general-purpose language model to produce relationship advice without a defined analytical framework. The language capability is connected to proprietary logic, domain-specific dimensions and a clear product purpose.
Jasmina Mohorn leads the development
Jasmina Mohorn created CDMA™ and developed the new LLM layer for Daty.ai. She brings more than ten years of hands-on technical and business architecture experience to the project, combining analytical design with the practical work required to turn complex logic into functioning systems.
Her professional background includes work connected to multiple United States patents and recognition through three Stevie Awards. Within Daty.ai, the same architect who created the compatibility framework is now developing the language layer that communicates its results. That continuity reduces the gap between methodology, software architecture and user experience.
Testing confirms the development direction
The latest CDMA™ upgrade incorporating the LLM has successfully completed the tests conducted so far. This supports the current development direction and allows the team to continue with broader validation and integration work.
The result should be understood as a development milestone rather than a final production-readiness claim. The next work will focus on explanation quality, consistency, edge cases, responsible use, technical integration and user testing before the capability is released more broadly.
Because relationship insights can influence personal decisions, Daty.ai is being developed as a decision-support system. Its outputs are intended to improve understanding, not to replace judgment or guarantee relationship outcomes.
A decade of technology development supports the milestone
The CDMA™ LLM development builds on a longer ZeeQuest technology path. Work that began with BaziWay and later Navigator created years of experience in personalized reports, compatibility analysis and timing-based insights. Between 2020 and 2022, more than 100,000 Personal Success Reports were produced through the earlier platform environment.
From 2024 through 2026, ZeeQuest concentrated technical resources on Daty.ai and the architecture required for a new generation of AI-supported intelligence. CDMA™, the Natal Engine and the Time Engine are being designed to work with data structures, application logic and AI interpretation as one coordinated product architecture.
The next development phase
ZeeQuest and the Daty.ai development team will now continue testing the language layer across a wider range of compatibility scenarios. The immediate priorities are to strengthen explanation consistency, refine the connection between CDMA™ outputs and generated language, and prepare the capability for controlled product testing.
Further updates will be published as defined validation and integration milestones are completed. The current result is clear: Daty.ai’s core Relationship Intelligence architecture is advancing, and ZeeQuest is converting proprietary concepts into tested technology components.
Explore Daty.ai technology and follow the next development milestones: https://daty.ai/technology
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