How Kernel is Decoding the Brain with Non-Invasive Neurotech

In the spring of 2016, backed by a bold wager from its founder, a new kind of neurotechnology startup emerged in Los Angeles. Kernel set out to give us the long-sought key to seeing and reading the brain, non-invasively.

The challenge Kernel tackles seems simple, but is very complex in reality: how do we translate neural activity into meaningful, measurable data without drilling into someone’s skull or using million-dollar machines? Most existing systems rely on implanted electrodes or grossly limited external sensors.

Kernel’s answer is an intersection of light and electricity, in the form of wearable helmets. Its flagship device, Kernel Flow, deploys time-domain functional near-infrared spectroscopy (TD-fNIRS) to fire infrared pulses through the scalp, tracking changes in blood oxygenation as a means to measure neural activity. What sets Flow apart is its high sampling speed (200 Hz) combined with spatial clarity that pushes the limits of what fNIRS can achieve.

This matters because the brain is relentless and fickle. In fields like mental health diagnostics, neurologic care, marketing insights, and emerging brain–machine interfaces, you need precision, speed, and spatial resolution to capture fleeting mental states. Kernel’s helmet doesn’t just see your brain, but also watches it think, feel, and remember. It measures how your mind lights up during a memory task, gauges anxiety signals in real time, and even supports clinical studies on Alzheimer’s and Parkinson’s dysfunction.

Why Kernel?

But what makes Kernel truly stand out isn’t just the sensors, but it’s their insistence on non-invasiveness combined with deployability. Unlike ground-penetrating implants (such as Neuralink or Synchron), Kernel’s Flow helmet can be used by researchers, clinicians, everyday consumers, and enterprise clients under Kernel’s neuroscience-as-a-service model. That means businesses can commission brain studies as easily as they might order a lab test, while remaining outside the boundaries of clinical trials.

Its proprietary blend of TD-fNIRS hardware, a robust software layer for translating raw signals into interpretable data, and real-world deployments gives it serious defensibility and requires navigating cross-domain expertise that very few possess.

Equally compelling is the investment story. Founder Bryan Johnson poured in $100 million of his capital upon launch, later contributing an additional $54 million by 2020. In mid-2020, Kernel closed a $53 million Series C primarily to expand commercial applications. More recently, in December 2023, it secured a $5.25 million Series D extension, part of a total $158 million raised over three rounds, backed by top-tier investors including Khosla Ventures and General Catalyst.

Future horizon

Looking ahead, Kernel’s roadmap is ambitious but thoughtfully paced. Its future hinges on driving down helmet costs (Johnson has mentioned a goal of smartphone-level pricing by 2030), and scaling deployments across health systems, research institutions, and enterprise clients.

In 2021, Johnson told Bloomberg, “To make progress on all the fronts that we need to as a society, we have to bring the brain online.” These aren’t marketing slogans; they chart a vision where non-invasive neural tools become as everyday as smartphones, powering new forms of insight, wellness, and augmented cognition. Its platform isn’t just another TBI. It's a foundational technology with the potential to transform neuromedicine, behavioral science, and human-AI interaction.