U.S. Patent Family Notice

1.  General Overview of MetaBrain Labs’ IP

The Framework:

MetaBrain Labs offers a modular AI framework designed for safe, real-time human-machine interaction between a system agent and a subject (human or machine) under evaluation. At its core, the system is rule-based to ensure reliability and compliance, especially in regulated settings like healthcare and research. But unlike rigid workflows, it is dynamic: machine learning models and large language models (LLMs) elevate the system’s adaptability, allowing each deployment to intelligently respond to changing subject states and environments. Clients can choose from prebuilt modules or add their own, customizing everything from user interface experiences to data sources to fit their specific needs.

What the technology does:

The system provides intelligent agents that assess and/or guide subjects based on real-time functional, physical, and contextual inputs. The system can detect patterns, validate responses, and adapt interaction flow based on evolving subject states. The experience may be delivered to a subject via text, voice, avatar (depending on the subject’s preference), or other data stream(s), and is ideal for applications like remote patient monitoring, workforce safety, mental wellness, performance optimization, IoT device management, and industrial monitoring. It works across sessions, building a longitudinal view of subject functioning.

How it works:

The platform blends structured agent scripting with AI-driven adaptability. Real-time (or near-real-time) sensor inputs (e.g., heart rate, motion, voice tone) and subject responses feed into an engine that unifies such data to create useful, contextualized data records. Based upon the unified data, the system analyzes, for example, a subject’s emotional state, engagement level, functioning, in light of contextual factors. Predefined safety rules may guide interaction boundaries, while AI models dynamically adjust the flow of queries or guidance directed to a subject, escalate risks or alerts, or refine or store insights. In human subject interactions, sentiment and signal analysis calibrate agent/subject interactions, and memory modules enable continuity across sessions. The result is a system that maintains trust and control while adapting fluidly to the subject.

The existing and expanding platform technology disclosed and claimed in the patents and applications of the patent portfolio cover numerous aspects of the vertical market use cases listed hereafter, particularly those aspects related to: conversational AI interfaces; real-time biometric, behavioral, or environmental sensor data; adaptive or automated decision-making; and personalized guidance, monitoring, and intervention.

2.  Patent Portfolio

The patent portfolio, and MetaBrain Labs’ covered software systems, are already non-exclusively licensed for remote patient monitoring and neuromarker identification field(s) of use.

Pending Adjustments to the Scope of MBL’s IP:

MBL currently has numerous pending US non-provisional and provisional applications that expand the scope of MBL’s patent claims beyond those claims issued in the ‘179 Patent – addressing a wider variety of platforms and systems where users input data that is contextualized to adapt the user engagement responsively and dynamically. Correspondingly, MBL’s functional IP (e.g., source code) has been, and continues to be, augmented for use in the vertical market uses cases summarized below. Through MBL’s strategic use of provisional and continuation-in-part applications, its patent portfolio will begin issuing patents with claim sets that reflect this broader scope of use cases.

Currently pending claim sets are directed to a digital system that evaluates responses received from subjects during an interactive query or guidance exchange between an intelligent agent and the subject. The system contextualizes each subject response with sensor-derived data accompanying the response and then evaluates what follow up actions should be taken, if any. Follow up actions may include modifying additional or future queries or guidance presented to the subject or escalating the interaction to a human operator of the system.

3.  Market Relevance

The technology market for precision medicine and digital therapeutics is poised for widespread adoption and exponential growth, driven by rapid advancements in wearable technology and AI-powered healthcare solutions – such as agentic AI. These innovative systems, which integrate AI-driven pattern recognition with biometric sensors and epigenetic analysis, enable highly personalized treatment plans by analyzing real-time physiological and genetic data to predict and address health conditions. Similar growth and advancements are occurring with other network connected sensor devices or arrays, in a wide variety of health, performance, environmental, and industrial applications. Further growth is also being fueled by public sector interest in increasing the role of “wearables” – sensor devices in the form of watches, bands, rings, patches, clothes, and “smart home” devices that can be used for a variety of applications including monitoring glucose levels, measuring activity levels, track heart health and observe sleeping pattern. The current Secretary of Health and Human Services recently made headlines when he announced that his agency was launching a campaign to encourage all Americans to use wearables to track health metrics.

The incorporation of secure data storage solutions, such as blockchain, may be relied upon to ensure compliance with stringent regulations like HIPAA and GDPR. With increasing consumer demand for tailored healthcare, and the proliferation of sophisticated wearables, the sector is experiencing a surge in investment and innovation, promising transformative outcomes in patient care and disease prevention, and positioning precision medicine and digital therapeutics as cornerstones of the future healthcare landscape.

4.  Vertical Market Use Cases

The MetaBrain Labs IP portfolio is applicable to and reads broadly across numerous enterprise and consumer use cases, including but not limited to:

Remote Patient Monitoring

Patient-facing agents gather behavioral data from patients in real time while also being connected to real-time sensor data of that patient.

Clinical Monitoring

Clinical intake agent collects vitals, charts symptoms, and ambient listening for emotional state, using biometric and voice data to guide triage and care actions.

Decentralized Clinical Trials

Sensor-triggered agent workflows that ensure participant engagement, symptom tracking, and protocol adherence in real time.

Industrial IoT & Operational AI

Factory and field agents that interpret sensor telemetry to guide human-machine interaction, predictive maintenance, and workflow adaptation.

Emotional Wellness & Mental Health

AI agents that respond to voice tone, facial expressions, and physiological markers to assist with stress regulation and behavioral support.

Sports & Performance Optimization

Real-time coaching and recovery prompts based on sleep, HRV, and strain— driven by live wearable input and user feedback.

Biofeedback & Mindfulness

Guided breathing, focus, or altered-state sessions triggered by real-time biometric signals such as EEG, HR, or respiration.

Child Wellness & Emotional Regulation

Game-based and voice-guided platforms that use sensor input to coach self-regulation and resilience in youth.

In-Vehicle AI Assistants

Drivers supported by biometric and behavior-sensing agents capable of triggering prompts or interventions during moments of fatigue or stress.

Ambient Health & Home Wellness

Context-aware agents that use smart home and wearable data to provide proactive wellness check-ins, reminders, and routines.

Cognitive Training & Education

Sensor-integrated learning platforms that adapt based on attention state, fatigue, or neural response in real time.

Workplace Readiness & Performance

AI assistants that monitor and coach knowledge workers and executives using biometric insights to optimize stress management and productivity.

Smart Glasses & Sensor-Driven Wearables

Voice and vision-based AI agents triggered by camera, movement, or mic data in AR, fitness, or health applications.

Security, Identity & Authentication

Conversational authentication using real-time voice and facial biometrics to verify identity and prevent spoofing.

Industrial IoT

Conversational authentication using real-time telemetry to guide management decision-making.

5.  Licensing Potential

MetaBrain Labs’ platform and patent portfolio have significant potential for licensing across multiple vertical markets and submarkets, due to its innovative integration of AI, biometrics, epigenetics, and metaverse technologies. Licensing to AWS, Meta, or IoT AI providers leverages their infrastructure, user base, and expertise to scale the technology. Anchor licensees in key IoT and vertical market segments may be candidates for exclusive field of use licenses – driving adoption across all relevant market segments. Additional licensees in non-obvious market verticals will anchor the IP into a number of seemingly unrelated markets where users input data that is contextualized to adapt the user engagement responsively and dynamically.