Glossary

Terms and definitions

Annotated Emotional and Psychological Cures

The use of data points or tags in training data sets that signal emotional states, such as "happy", "frustrated", and "anxious", or psychological contexts, such as urgency and confusion.

For example:

• Emotional Cues: A comment like "I really appreciate this!" can be annotated as a "positive emotion".

• Psychological Cues: A message like "I don't know what to do next" might can be labeled as "confusion" or "seeking help".

These annotations allow AI models like LLMs or AI agents to learn how to interpret and respond to human emotions and mental states more accurately, which adds a layer of empathy and relevance to their outputs.

Affective Computing

A branch of computing that focuses on the development of systems and devices capable of recognizing, interpreting, and responding to human emotions in real-time.

Affective Computing by Virtue is our proprietary product line that enables you to make your AI solutions human-centered, empathetic, and ethically aligned.

AI-Powered Solutions

Technological systems or platforms that use artificial intelligence to automate, enhance, and deliver results.

Affective Computing by Virtue can enhance AI-powered solutions by integrating emotional intelligence, which enables them to provide ethical, human-centered outcomes.

Auto Logic

A core feature of Virtue’s platform that continuously learns and evolves from real human feedback. It personalizes customer journeys in real-time, reducing the need for manual updates.

Behavioral Input Processing

The analysis of behavioral data such as the time taken to answer a question or the action of a user scanning a QR code.

This functionality enables the system to adapt to user actions for personalized responses.

Cognition Explorer

A functionality of the platform that performs real-time psychological assessments, analyzing emotions such as frustration or excitement. It dynamically adapts tone, pace, and content to enhance user engagement.

Customer Experience (CX)

The interaction between a customer and a company’s product, service, or solution.

Virtue’s tools enable real-time emotional insights to create human-centered CX strategies.

Digital Twin

A virtual representation of a physical object, system, or process.

Solutions powered by Affective Computing by Virtue's Simulation series incorporate the concept of digital twins to simulate human interactions and predict emotional and psychological responses.

EDAA™ (Emotional Data Analysis and Automation)

Virtue’s proprietary multimodal foundational deep-learning AI model that integrates emotional intelligence into AI systems. It bridges the gap between data-driven insights and human-centric interpretation.

Key Features

• Emotional Intelligence: Analyzes unique psychological patterns.

• Bias-Free Decisions: Uses metacognition engines for unbiased outcomes.

• Privacy-First Design: Implements military-grade encryption and GDPR compliance.

Emotional Empowerment

The integration of emotional intelligence into AI systems, enabling them to recognize, interpret, and respond empathetically to human emotions.

For example, a virtual therapist can use emotional empowerment to detect signs of distress in a user’s text or tone and adjust its responses to provide comfort and guidance.

Emotional Intelligence (EI)

The capability of a system to understand, interpret, and respond to human emotions. Solutions powered by Affective Computing by Virtue leverage EI to enhance user experience and build trust.

Environmental Input Processing

The ability to process environmental data, such as location, speed, and crowd density. This data helps tailor interactions to the user’s context.

Ethical Prompt Engineering

The crafting of AI prompts to generate fair and unbiased responses that are aligned with ethical guidelines. This process ensures that outputs reflect societal values and avoid harm.

For example, a legal AI assistant can use ethically designed prompts to summarize contracts without introducing biased interpretations or oversimplifications.

Generative Capabilities

The ability of AI systems to create actions, logics, and solutions dynamically based on real-time feedback and interaction data.

Human-Powered AI Solutions

AI solutions that are designed to amplify human capabilities by understanding and responding to human emotions, needs, and motivations in real-time. These solutions prioritize ethical and empathetic interactions.

Hyper-Personalization

The creation of experiences tailored to individual users through behavior, preference, and context analysis. It ensures that interactions feel deeply relevant and human-centered.

For example, an e-commerce platform can use hyper-personalization to recommend products based on a user’s browsing habits, past purchases, and real-time emotional cues.

Hyper-Specific Customization

An advanced level of tailoring AI systems to address niche or highly specialized needs that focuses on granular requirements for specific use cases or industries.

For example, an educational platform can customize its AI tutor to adapt lesson plans for students with learning disabilities and offer tailored teaching strategies.

Interaction Automation System (IAS)

A system that predicts and automates the best actions for individual users, ensuring intuitive and tailored interactions.

Liquid Ethics

A forthcoming product series from Virtue that provides real-time ethical assurance for AI actions. It ensures fairness, transparency, and prioritization of mental and emotional safety.

Low-Code API

A solution development approach that enables users to integrate and customize solutions with minimal coding effort. Virtue’s APIs provide direct access to its platform for scalable, tailored solutions.

Mind Pulse

A functionality that analyzes real-time emotional data to provide deeply personal and engaging interactions and ensures that responses resonate with users' feelings.

Mood Match

A feature that detects and matches user emotions to appropriate system responses and enhances personalization and engagement.

Multimodal Emotional Analysis

The process of analyzing data from multiple behavioral, emotional, and environmental sources to accurately interpret human emotions.

No-Code Portal

Our graphical user interface (GUI)-based platform that requires no coding skills to use.

It allows users to build, manage, and monitor solutions using Virtue’s tools, which are powered by the EDAA™ framework.

Orchestra

Virtue’s core platform for integrating, managing, and deploying AI-powered solutions. It supports both no-code and low-code approaches for seamless customization and scalability.

Persona Profiling

The creation of user profiles by asking specific questions to understand individual characteristics, preferences, and needs.

Post-Customization

The adaptation of AI models after initial deployment to meet specific user needs or industry requirements. This ensures that the AI remains effective and contextually relevant.

For example, a language model trained for general use is fine-tuned to understand medical terminology, enabling it to assist doctors and nurses with patient documentation.

Pre-Validation

A process to test AI models and systems before deployment, ensuring they align with ethical, functional, and contextual standards. This often involves simulations and scenario testing.

For example, a digital twin simulates customer service interactions with an AI assistant to detect potential biases or inappropriate responses before it goes live.

Psychological Input Processing

Analyzing psychological inputs such as speech vectors, heart rate, and EEG signals to build accurate user profiles and adapt interactions accordingly.

Real-Time Data Processing

The ability to analyze and respond to data as it is generated.

Solutions powered by Affective Computing by Virtue process emotional and psychological data in real-time without storing sensitive information.

Regular Interaction

A feature that dynamically adapts responses to user emotions and psychological cues during live interactions.

Regular Interaction creates emotionally intelligent, human-centered experiences that enhance trust and engagement in real time.

Reinforcement Learning with Human Feedback (RLHF)

A training method where human evaluators provide feedback on AI responses to improve their relevance, accuracy, and ethical alignment.

For example, a healthcare chatbot can be trained using RLHF to prioritize empathetic responses when addressing sensitive topics like mental health or chronic illness.

Simulation (Validation)

The use of digital twins to test prototypes and strategies and predict authentic human emotional and psychological responses before real-world implementation. This reduces risks and optimizes outcomes.

Simulation (Coaching)

Training generative models, such as large language models (LLMs), using simulated scenarios to enhance their responsiveness and empathy in real-world interactions.

VaaS (Validation-as-a-Service)

A service that provides external validation of AI systems to ensure they meet ethical, compliance, and operational standards without requiring in-house resources.

For example, a FinTech company can use VaaS to validate its fraud detection AI for regulatory compliance and unbiased decision-making.

vEd

A Virtue product designed to empower educational institutions by integrating emotional intelligence into EdTech solutions. It personalizes learning experiences based on students’ psychological profiles.

vSafe

A Virtue product aimed at mitigating risks in operational environments by identifying and addressing emotional, psychological, and environmental factors in real-time.

vSense

A Virtue product that provides real-time insights into customer emotions and needs. It enables dynamic adjustments in CX strategies to enhance engagement and loyalty.

Virtual Human

A simulated human persona that interacts with users or systems, incorporating psychological and emotional insights to create authentic and empathetic connections.