- Remove the current class from the content27_link item as Webflows native current state will automatically be applied.
- To add interactions which automatically expand and collapse sections in the table of contents select the content27_h-trigger element, add an element trigger and select Mouse click (tap)
- For the 1st click select the custom animation Content 27 table of contents [Expand] and for the 2nd click select the custom animation Content 27 table of contents [Collapse].
- In the Trigger Settings, deselect all checkboxes other than Desktop and above. This disables the interaction on tablet and below to prevent bugs when scrolling.
Most technology companies in the hardware space face the same problem: building a great product is hard, but building distribution is even harder. Neurable's answer is to not compete for distribution at all — and instead become the intelligence layer inside hardware that already has it.
That's the OEM licensing model. Here's what it means and why it matters.
What OEM licensing means
OEM stands for original equipment manufacturer. In an OEM licensing relationship, a technology provider licenses its technology to a hardware maker, who integrates it into their own product and brings it to market under their own brand.
You see this model everywhere in technology. Qualcomm licenses Bluetooth chip designs. Dolby licenses audio processing. ARM licenses processor architectures. The underlying technology powers products from dozens of manufacturers — without the licensor needing to build, brand, or distribute a single end product themselves.
Neurable is applying the same model to cognitive tracking and EEG sensing. We build the technology — the sensors, the AI, the cognitive intelligence platform. Hardware partners integrate it into their products. Their brand goes on the box. Their distribution gets the product to consumers.
Why this model makes sense for cognitive wearables
Cognitive wearables need to be wearables first. If the device isn't comfortable, well-designed, and useful on its own merits, no one will wear it — and a device no one wears generates no data and no value.
Consumer hardware brands have already solved this problem. They've built manufacturing capabilities, supply chains, retail relationships, and brand trust with millions of consumers. Neurable's technology makes their products meaningfully better. Their infrastructure makes Neurable's technology accessible at scale.
It's a better division of labor than trying to build and sell hardware from scratch — and it creates a faster path to deployment than either team trying to execute independently.
What OEM partners actually get
When a hardware brand licenses Neurable's platform, they get:
- Embedded EEG sensing hardware, engineered for their product form factor
- Real-time cognitive AI — focus, fatigue, mental load — running in real time
- A software development kit for building cognitive-aware features and applications
- Access to Neurable's proprietary AI models, continuously improved as the dataset grows
The result is a device that doesn't just play audio or track steps — it understands the cognitive baseline of the person wearing it, and can adapt experiences accordingly.
Why it matters for the market
The OEM model means cognitive wearables can scale at the speed of the consumer electronics market — not at the speed of a single startup's ability to build and sell hardware. It means the technology reaches more people, generates more data, and improves faster.
It also means the business model is fundamentally different from a consumer hardware play. Revenue is recurring and tied to platform adoption, not unit economics on individual devices. The more partners, the more data. The more data, the better the AI. The better the AI, the more valuable the platform becomes to the next partner, and their end user.
That's a flywheel. And it's already spinning.
2 Distraction Stroop Tasks experiment: The Stroop Effect (also known as cognitive interference) is a psychological phenomenon describing the difficulty people have naming a color when it's used to spell the name of a different color. During each trial of this experiment, we flashed the words “Red” or “Yellow” on a screen. Participants were asked to respond to the color of the words and ignore their meaning by pressing four keys on the keyboard –– “D”, “F”, “J”, and “K,” -- which were mapped to “Red,” “Green,” “Blue,” and “Yellow” colors, respectively. Trials in the Stroop task were categorized into congruent, when the text content matched the text color (e.g. Red), and incongruent, when the text content did not match the text color (e.g., Red). The incongruent case was counter-intuitive and more difficult. We expected to see lower accuracy, higher response times, and a drop in Alpha band power in incongruent trials. To mimic the chaotic distraction environment of in-person office life, we added an additional layer of complexity by floating the words on different visual backgrounds (a calm river, a roller coaster, a calm beach, and a busy marketplace). Both the behavioral and neural data we collected showed consistently different results in incongruent tasks, such as longer reaction times and lower Alpha waves, particularly when the words appeared on top of the marketplace background, the most distracting scene.
Interruption by Notification: It’s widely known that push notifications decrease focus level. In our three Interruption by Notification experiments, participants performed the Stroop Tasks, above, with and without push notifications, which consisted of a sound played at random time followed by a prompt to complete an activity. Our behavioral analysis and focus metrics showed that, on average, participants presented slower reaction times and were less accurate during blocks of time with distractions compared to those without them.
