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Domain Specific 
Virtual Agent

Achieve More, Achieve Faster 

The IQ-110 is a sophisticated digital assistant designed to not only understand but also to make informed decisions. It is anchored on advanced foundational models, including LLMs and others, that have been meticulously fine-tuned with your enterprise's specific datasets, ensuring tailored insights and actions. Its ability to connect to online resources is facilitated by its dynamic API integration layer, empowering the IQ-110 to seamlessly interface with various digital platforms. This allows for the constant ingestion of real-time data, ensuring its knowledge bank remains updated. Beyond being just a passive receptor of information, the IQ-110 is equipped with a proactive task execution engine. This engine leverages insights from the foundational models to initiate and manage tasks, always striving for optimal outcomes. A key feature of this engine is its capability to chart the best courses of action based on the available data. The IQ-110 incorporates a feedback mechanism, enabling continuous refinement of its operations. This ensures the assistant's intelligence isn't static; rather, it evolves with each interaction, becoming smarter and more efficient over time. Enhancing the user experience is a comprehensive dashboard that provides a panoramic view of the diverse interactions orchestrated by the IQ-110.

IQ-110 Features 

  • Enhancing Human-Machine & Machine-Machine Interaction

  • Enabling Support for Complex Tasks

  • Facilitating Amorphic Missions

  • Empowering Amorphic Teaming Missions

  • Adapting to First-Time-Seen Environments

  • Incorporating Embedded Low-Fidelity World Models

  • Integrating Embedded Domain-Specific Knowledge Graphs (KG)

  • Utilizing Large Language Models (LLMs) for Reasoning and Decision-Making

  • Implementing Abstract Low-Latency Planning

  • Accepting Input via Semantic Interfaces (Objects)

  • Delivering Output Through High-Level Actions (Actuators)

  • Providing Real-Time Adaptation to Changing Scenarios

  • Ensuring Energy Efficiency with Optimized Performance Algorithms

  • Enhancing Security Measures Through Advanced Encryption

  • Facilitating Seamless Integration with Existing Systems

  • Enabling Remote Monitoring and Control

Use Cases

IQ-130 is a special add-on designed to make many types of robots smarter and more capable. It can be applied to:

  • Service Robots: Assisting in hospitals, hotels, and customer service roles.

  • Industrial Robots: Improving efficiency in factories and production lines.

  • Warehouse Robots: Sorting and moving items, aiding in inventory management.

  • Home Robots: Helping with cleaning, cooking, and general household tasks.

  • Search-and-Rescue Robots: Assisting in locating and helping people during emergencies.

  • Agriculture Robots: Managing crops, watering, and pest control in farming.

  • Mining Robots: Exploring and extracting resources deep underground.

  • Construction Robots: Assisting in building, maintenance, demolition, and site preparation.

  • Retail Robots: Managing inventory, checkout, customer guidance, and in-store support.

  • Scientific Research Robots: Conducting experiments, data collection, and lab automation.

  • Space Exploration Robots: Performing tasks in space travel, planetary exploration, and satellite maintenance.

With IQ-130, these robots can adapt to new or complex situations, collaborate with each other, work alongside humans seamlessly, and execute tasks with greater accuracy and efficiency. 


Our IQ-130 solution offers several advantages over rule-based systems.

  • Flexibility: IQ-130 is more flexible because it can handle complex and diverse tasks.IQ-130 handles tasks with multiple goals, conditions, and subtasks, whereas rule-based systems are limited to tasks with a fixed sequence of decisions.

  • Reusability: IQ-130 can reuse the same hierarchical structure for different tasks. In contrast, rule-based systems require a new decision tree to be created for each new task.

  • Robustness: IQ-130 is more robust than rule-based systems because it can handle incomplete or missing information. Rule-based systems require all information to be available at each decision point.

  • Scalability: IQ-130 can scale better than rule-based systems because it use a hierarchical structure that can be decomposed into smaller, manageable tasks. In contrast, rule-based systems can quickly become unwieldy and difficult to manage as the number of decisions and paths increase.

  • Human-Like Reasoning: IQ-130 can model human-like reasoning, which makes it easier for people to understand and interact with them. Rule-based systems are limited to a fixed set of rules and cannot adapt to new situations or unexpected events.

  • Modularity: IQ-130 can be modular, meaning that different parts of the planning process can be modified or replaced without affecting other parts. This makes it easier to update or change specific components of the planning process without having to overhaul the entire system.

  • Goal-Directedness: IQ-130 is goal-directed, meaning that they focus on achieving specific goals rather than following a fixed sequence of decisions. This makes it more efficient at finding solutions to complex problems.

  • Re-planning: IQ-130 can handle changes in the environment or new goals by re-planning and adjusting its hierarchy of tasks. This makes it more adaptable to changing circumstances and requirements.

  • Learning: IQ-130 can learn from experience and improve its performance over time. This is particularly useful in dynamic and uncertain environments where the planner must continually adapt to new information.

  • Domain-Specificity: IQ-130 can be designed to be domain-specific, meaning that it can be tailored to specific industries or applications. This makes it more efficient and effective in those domains.

  • Plan Execution: IQ-130 can handle the execution of plans, not just the planning process itself. This means that it can monitor the environment and adjust the plan in real-time based on feedback from sensors or other sources.

  • Multi-Agent Systems: IQ-130 can be used to coordinate the actions of multiple agents in a multi-agent system. This is particularly useful in applications such as robotics, where multiple agents must work together to achieve a common goal.

  • Interpretability: IQ-130 is more interpretable than rule-based systems, meaning that it is easier to understand how the planner arrived at a particular solution. This can be useful for debugging and improving the planner's performance.

  • Uncertainty Handling: IQ-130 can handle uncertainty and ambiguity in the planning process. This is important in applications where the environment is uncertain, or the planner has incomplete information.

  • Complexity Handling: IQ-130 can handle complex tasks that require reasoning at multiple levels of abstraction. This makes it well-suited for applications such as scheduling or logistics, where there are many interrelated tasks to be managed.

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