Licensing
Dialogic AI licenses cognitive middleware that gives generative systems a stable self: identity continuity, emotional regulation, and transparent reasoning, implemented as a declarative cognitive architecture rather than conventional prompting or model modification.
Licensed UCPM Components
Core Framework
The Unified Cognitive-Personality Model (UCPM): the foundational cognitive-personality architecture that governs identity, affect, memory interpretation, and reasoning continuity.
Specialization Template
A structured configuration system for instantiating personas, domains, or agents, including training materials on the design of dialogic entities and framework customization.
Dialogic Interpretation Frameworks (DIFs) enable lawful, interpretable simulation of systems, scenarios, and worlds through structured dialogue.
DIFs are developed by Dialogic AI in collaboration with each customer to reflect the target domain’s rules, states, and transitions. The resulting framework is delivered under license according to agreed terms and conditions.
Dialogic Simulation Frameworks (DIFs)
How it Fits in Your Stack
Application / Agent
Dialogic AI layer (UCPM or domain-specific DIF)
Foundation Language Model (GPT, Gemini, Claude, LLaMA, etc.)
Infrastructure (cloud / on-prem)
UCPM and DIFs govern interpretation, identity, and reasoning; the foundation model remains responsible for language generation.
How Engagement Works
Initial Contact – Reach out via the contact information provided below
Evaluation – Custom demo using a defined persona and question set, delivered as a transcript
Pilot License – Scoped integration under NDA and letter of intent
Production License – Full platform or product embedding
Demonstrations are conducted for evaluation purposes and are not (generally) provided as contractual development services.
Implementation Model
Although UCPM and Dialogic Interpretation Frameworks are expressed declaratively in text, they are not conventional prompts and do not operate as orchestration middleware or inference-time hooks.
Traditional prompting prescribes what a model should say next. UCPM defines a stable interpretive constitution: how the system models itself, regulates affect, maintains identity, and reasons coherently across interactions.
UCPM does not intercept tokens, modify inference pipelines, or alter model internals. It operates entirely at the semantic–interpretive layer, establishing lawful constraints that the model itself evaluates and enacts over time, independent of API, runtime, or hosting environment.