GlassView is powered by Cogwear, clinical-grade brain imaging at scale spun out of UPenn Medicine, and built through advertising scale. We connect neural signals captured during real exposure with verified behavioral outcomes across media environments.
Most neuroscience happens in controlled settings with small samples. Most advertising happens at massive scale with no brain-behavioral signal. GlassView connects both, creating a validated loop between clinical-grade brain imaging and real-world behavioral outcomes at population scale.
"Studies have repeatedly shown that directly measuring the brain for engagement, emotion and memory in even just a handful of volunteers can predict the behavior of millions of people along a variety of dimensions from click-through-rates to sales. It's the trifecta of consumer psychology."
Dr. Michael L. Platt · Co-founder, Cogwear · Director, Wharton Neuroscience InitiativeParticipants wear Cogwear's EEG headband, a clinical-grade device spun out of UPenn Medicine, home to the first clinical-grade neurology department in the United States, developed in collaboration with the Wharton Neuroscience Initiative and supported by the National Science Foundation and the NIH. The device captures neural signals associated with engagement, emotional response, memory encoding, focus, and fatigue in real time under naturalistic conditions.
Those neural signals are paired with real behavioral outcomes from GlassView's advertising platform: purchases, visits, conversions, and other campaign objectives. Brain activity and real-world decisions are connected through the same participant pathway. This is the validation loop that conventional laboratory work does not have the commercial infrastructure to build.
The validated rule library trained on Layers 1 and 2 is applied across GlassView's full platform reach: 2.7 billion people across connected screens including streaming, digital video, connected TV, audio, AR, and emerging spatial platforms. Each new campaign adds another layer of replication evidence to the corpus.
Laboratory neuroscience is precise, but it rarely follows the same person from exposure to verified marketplace behavior. Survey and click signals operate at scale, but they cannot show the human response at the moment of exposure.
GlassView links both. The same participant pathway. The same exposure window. Emotional response and behavioral outcome, paired. That pairing is what makes the signal library distinct, and what makes the models trained on it more useful than isolated reporting.
Clinical-grade dry EEG sensors capture neural activity in real time. Comfortable, wearable, no lab required.
Signal patterns associated with engagement, emotional arousal, memory encoding, focus, and fatigue are captured moment by moment during exposure.
Purchases, visits, conversions, and engagement decisions are recorded through GlassView's platform and third-party partners.
Patterns that hold up across multiple campaigns enter the canonical rule library. Patterns that fail to replicate are demoted out of it. The corpus accumulates only the signal that survives repeated validation.
The neurotechnology field has long had powerful sensing technology and rigorous laboratory science. What it lacked was the bridge connecting neural signal to real-world human behavior at population scale. That bridge requires infrastructure no institution could build alone: millions of impressions, millions of verified outcomes, and the commercial reach to deploy signal capture outside controlled settings. GlassView provides that bridge.
Brain-behavioral intelligence that performs.
GlassView's core platform applies emotional intelligence to advertising in real time. The Emotional Intelligence Engine captures what audiences feel during exposure and connects that signal to the media conditions that drive performance. The result is advertising optimized through real human response, not only screen-level proxies. GlassView works with over 80 of the world's top Fortune 100 brands across every connected screen, delivering reach of 2.7 billion people globally.
A foundation brain health applications require.
Detecting changes in cognitive function depends on understanding healthy cognitive patterns across a large, diverse, and representative population. That baseline has not existed at scale outside controlled environments. GlassView's platform generates neural signal from ordinary people under naturalistic conditions, creating a population-level reference library that future brain health models may require. Cogwear is an NIH-funded UPenn Medicine spinout with brain health applications in development, including cognitive monitoring and early neurological detection.
Helping machines understand brain signals well enough to advance assistive technology.
Non-invasive brain-computer interfaces aim to translate intention into control of assistive devices without surgery, implants, or a laboratory. The sensing technology exists, but reliable decoding requires training signal at greater scale and diversity. GlassView's brain-behavioral signal library may help provide part of the foundation those future systems require. The path is not a straight line from advertising to motor control, but both depend on turning noisy human brain signals into patterns that models can learn from.
What physical metrics miss.
Elite athletic performance is not only physical. Focus, decision speed under pressure, emotional regulation during competition, and cognitive recovery after exertion are all brain-behavioral phenomena that wearable EEG can capture outside controlled settings. Cogwear already has applications in sports safety and human performance monitoring, including concussion detection and fatigue tracking in high-impact sports.
In an era when artificial intelligence is reshaping every software-dependent industry, the companies most exposed are pure intermediaries: businesses where an AI model can synthesize similar outputs without proprietary inputs. GlassView is structurally different. Its competitive position is protected by two moats that deepen with every campaign served.
The only way to obtain a human neural signal is to place a sensor on a human head. No language model, generative system, or synthetic pipeline can manufacture what Cogwear's clinical-grade EEG hardware physically captures. The signals at the foundation of GlassView's platform originate from real people, in real time, through proprietary hardware operating under an exclusive advertising and media license.
As AI capabilities advance, the value of genuinely proprietary sensor signal increases. Every competitor without access to clinical-grade wearable EEG at advertising scale faces the same constraint: they cannot capture the signal. GlassView can.
The value of GlassView's signal library is not the raw neural signal in isolation. It is the pairing of those signals with millions of verified real-world outcomes: purchases, visits, conversions, and engagement decisions recorded across 910 billion video views and a global audience of 2.7 billion people. That validation history is cumulative and difficult to replicate from a standing start.
A competitor entering this space would need years of commercial operation at global scale simply to begin building the behavioral validation layer GlassView has already constructed. The moat widens with every campaign because every campaign adds another layer of brain-behavioral pairing.
The hardware moat ensures that the behavioral validation moat can only be built by GlassView in advertising and media. The behavioral validation moat means that even if a competitor accessed comparable hardware tomorrow, they would begin with no validated signal library and no trained models. The longer the platform operates, the more expensive competitive entry becomes.
James S. Riepe University Professor of Neuroscience, Psychology & Marketing, University of Pennsylvania · Director, Wharton Neuroscience Initiative · Perelman School of Medicine
Dr. Platt is one of the world's foremost neuroscientists studying decision-making, social behavior, and the biological mechanisms underlying human cognition. As a Penn Integrates Knowledge professor, he holds simultaneous appointments in the Perelman School of Medicine's Neuroscience Department, the School of Arts and Sciences' Psychology Department, and the Wharton School's Marketing Department.
His work has been supported by the National Institutes of Health, the Department of Defense, the Klingenstein Foundation, the McDonnell Foundation, and the Simons Foundation, and has been collectively cited over 23,000 times in peer-reviewed scientific literature. He is a former President of the Society for Neuroeconomics and has served on the World Economic Forum Global Future Council on Brain Science.
Dr. Platt co-founded Cogwear Technologies to move clinical-grade brain science from the laboratory into the real world and serves on GlassView's advisory board, providing the scientific foundation for GlassView's neural signal methodology.
Medical Device Executive · 25+ Years in Medical Device Industry · 54 Patents · Formerly Boston Scientific, DSM Biomedical, ev3, American Medical Systems
David Yonce leads Cogwear Technologies as CEO, bringing more than 25 years of medical device industry experience to the task of moving clinical-grade brain technology from the laboratory into scalable commercial applications. He has positioned companies for double-digit growth and acquisition, helped bring over 50 new products to market, and holds 54 patents.
His background spans R&D, operations, marketing, strategy, and sales at companies including Boston Scientific, American Medical Systems, ev3, and DSM Biomedical, where he served as VP and Global Head of Innovation. He has testified before the Pennsylvania State Senate on AI utilization in biotechnology and counsels industry advocacy groups and public seed fund initiatives.
Under David's leadership, Cogwear is expanding commercial applications across advertising, athletic performance, and cognitive monitoring, with a long-term roadmap in brain health rooted in the company's NIH-funded UPenn Medicine origins.
Clinical-grade neurotechnology spun out of UPenn Medicine, home to the first clinical-grade neurology department in the United States.
Cogwear's EEG headband is designed to look and feel like a comfortable athletic headband. Inside, proprietary brain imaging sensors, machine learning, and breakthrough neuroscience work together to deliver clinical-grade neural signals anywhere, anytime, without a laboratory.
Pioneered together with neuroscience experts from the University of Pennsylvania and supported by the National Science Foundation and the National Institutes of Health, Cogwear brings clinical-grade brain science out of the lab and into the real world. UPenn Medicine is a Cogwear stakeholder, structurally linking the company to its scientific origins.
GlassView is Cogwear's largest corporate shareholder and holds an exclusive license for Cogwear's technology in advertising and media applications, the commercial foundation that funds Cogwear's broader development in health, diagnostics, and human performance.
Proprietary brain imaging sensors capture electrical brain activity comfortably and accurately. No gel, no lab, no wires.
Engagement, emotion, memory encoding, focus, and fatigue captured millisecond by millisecond and delivered through a secure app and shareable dashboard.
Unlike laboratory EEG requiring controlled environments, Cogwear captures clinical-grade signal in real-world settings while sitting, moving, working, watching, and living.
Developed in collaboration with neuroscience experts from the University of Pennsylvania, with support from the National Science Foundation and the National Institutes of Health.
GlassView's mission is to drive performance through brain-behavioral intelligence on every connected screen. Our higher order mission is to fuel brain health, one media campaign at a time.
Neural signals from clinical-grade Cogwear EEG hardware, validated against millions of real behavioral outcomes, applied across 2.7 billion viewers.
Cogwear, an NIH-funded UPenn Medicine spinout, is advancing cognitive monitoring, anxiety, and depression applications, with GlassView's population-scale behavioral signal library as part of the validation foundation.
Population-scale, behaviorally validated neural signal that may help train the next generation of non-invasive brain-computer interfaces.
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