#StartupsEverywhere: New York, N.Y.

#StartupsEverywhere: Mariam Khayretdinova, CEO & Founder, Brainify.AI

This profile is part of #StartupsEverywhere, an ongoing series highlighting startup leaders in ecosystems across the country. This interview has been edited for length, content, and clarity.

Accelerating Neuroscience Research Through AI

Based in New York, Brainify.AI is developing a brain data platform that combines portable Electroencephalography (EEG) hardware with AI to help create more effective treatments and diagnostics for neurological conditions. We sat down with Mariam Khayretdinova, founder and CEO, to discuss her experience navigating data privacy regulations, fundraising, and patents.

Tell us about your background. What led you to Brainify.AI?

My background is quite diverse. I started as an applied mathematician, which was my first master's degree, before spending 12 years in tech, developing solutions across a wide range of industries from the automotive to investment banking.

My last role was at Bright Box, which was acquired by Zurich Insurance, giving us a successful exit. After that, I decided to make a deliberate pivot. I enrolled at Harvard Extension School, earned a master's degree in psychology, and connected with professors who asked to collaborate on a joint research project between Harvard Medical School and Wheaton College. That experience introduced me to academia and the research side of things for the first time.

That intersection of neuroscience and technology is what sparked the idea for Brainify. The core mission was to accelerate neuroscience research using modern technology and mathematics—what we now call AI.

What is the work you all are doing at Brainify.AI?

Brainify is a brain data platform designed to help develop better medications and more effective diagnostic tools. At its core, Brainify collects EEG data, stores it in a single, unified data repository—cleaned, synchronized, and harmonized—so it can be used for AI applications. From there, we have a foundational model trained on half a million patients, which pharma companies can leverage to develop better biomarkers in their drug development process. For example, identifying which patients a particular drug is likely to work for, or building better diagnostic tools in the brain health space.

The reason there are so few diagnostics based on brain data today, frankly, almost none, comes down to a lack of data. Not just any data, but data that truly represents the global population: diverse across countries, ages, sexes, life experiences, and sicknesses. The brain is an extraordinarily complex organ, and most studies conducted so far have examined only 200 or 300 brains, far too small a sample to be meaningful at scale. Brainify is working to change that. Our goal is to collect global brain data that genuinely represents the population at scale, making the understanding of the brain more accessible and actionable for everyone working in the field.

Our device is an EEG system, a cap with electrodes that you place on a patient's scalp to collect electrical activity from the brain. The key differentiator is our amplifier, which is very small and portable. The whole setup can be placed on a patient in about five minutes; it's lightweight, and comes with a portable laptop for the doctor. What Brainify.AI adds on top is immediate AI-driven analysis, so you don't need a specialized EEG technician to do the readouts.

How have data privacy regulations and data localization requirements impacted your business?

This is something I speak about a lot because it's more complicated than people realize. Every single country has its own regulations, especially around brain data, and some of those regulations were made by people without thinking about the future, without understanding the medical field, or without specifically understanding AI.

I'll give you an example with the General Data Protection Regulation, where brain data is considered personal data. As a result, you need extensive consents,  you cannot buy this sort of data, and you cannot work with it outside the EU. I understand and agree with the need and desire to protect specific individuals, but inflexible rules pose real constraints that aren’t connected with what is needed to innovate. We don't really need personally identifiable data for foundation models because we're not interested in a particular John Doe. Instead we need EEGs, brain scans, and related information that impacts the brain like their gender, approximate age, what country they live in, their history of illness, and what medications they've been taking. Without having access to this data, we will never understand how the brain works. That means we will never find treatments for Parkinson's, for Alzheimer's, or have great diagnostics.

Also, the costs associated with these policies requiring the data to stay local are huge. You need to open new servers, create facilities for locally stored data, and hire people who are specifically certified to handle this data. I have to negotiate with every single player, meet different protection requirements in every jurisdiction, and find ways to train models across all of it, losing quality, speed, and accuracy in the process.

What has the fundraising journey been for Brainify.AI? Have you encountered any barriers in your path?

Brainify.AI has raised $4M to date across European and American funds, both angel and VC. We've also secured non-dilutive credits from data companies to support AI development. However, none of our funding comes from government grants. 

Government grants are extremely challenging for operating companies like mine. The process takes nine months or more, during which your company must survive. These programs mainly suit early-stage founders, like PhD students with an idea. For us, applying would mean diverting resources, hiring grant specialists, and enduring long waits. With ten full-time employees, mostly engineers, we concluded that government funding doesn’t align with our realities or needs.

We're really grateful to every investor who's been supporting us along the way. But I have to be honest, the fundraising environment for biotech has not been friendly. And that's not just what we're seeing. Other founders are sharing the same experience.

I think a few things are driving this. The mega-rounds in AI companies have absorbed a lot of the capital that would otherwise reach early-stage companies, including biotech. On top of that, fundraising has been tough for VCs themselves, coming off weak performance in the space after 2021-2022, which I imagine hasn't made it easier to keep LP confidence. The global political situation hasn't helped either.

For Brainify.AI specifically, our biggest challenge is that we don't fit neatly into most VC theses. We sit at the intersection of medical devices, data infrastructure, AI, and drug development. It can be hard for investors to evaluate us through a single lens, and there's no easy way to simplify what we are. Our solution grew as a response to what the market actually needed, not around a clean category.

Have you considered any intellectual property strategies for your company?

Yes, we've filed patents on both our algorithms and the device. But like most founders, we made mistakes along the way. Great patent lawyers with deep domain expertise are expensive, and early-stage startups often can't afford them. On top of that, the filing and review process is very lengthy. By the time you get initial feedback, file revisions, and finally receive a grant, years can pass. And a lot can happen to a company in that time.

There's also a less obvious problem. In a fast-moving field like AI, a published patent application can actually work against you before it's granted. It gives competitors access to your approach, and they can adjust the technology just enough to fall outside the patent scope. So increasingly, treating core IP as a trade secret feels like a smarter strategy, at least until the system catches up with a way to protect against that kind of workaround.

At the same time, some investors still expect patents to already be in place, without fully accounting for these realities. So you end up navigating between two sets of expectations that don't always align.

Are there any local, state, or federal startup issues that you think should receive more attention from policymakers?

I wish there were more government programs supporting medtech and biotech companies, whether through access to data, access to institutions that can help with. I wish there were more government programs supporting medtech and biotech companies, whether through access to data, access to institutions that can help with data collection, or just better infrastructure around both.

For example, I'd love to see more investment in preventive healthcare, like including EEGs as part of basic annual diagnostics. That's not only good for population health, it also generates the medical data we need to build better diagnostic tools. Right now, we're in a real medical data crisis. In psychiatry, there are no standardized protocols. Every psychiatrist works differently, some leave detailed notes, some leave nothing. Government investment in data storage infrastructure and standardized protocols for collecting and sharing data between clinics and hospitals would benefit the whole ecosystem, not just startups, and lead to better health outcomes.

I'd also point to the need for more support for U.S. startups internationally. When I've attended events like BIO Japan or the World Health Expo in Dubai, other countries do a great job showcasing their early-stage startups. The U.S. presence could use more of that, and I think there's a real opportunity to help startups navigate and participate in those events more easily. It ties back to the broader issue: even when government resources exist, they often don't work well for startups.

All of the information in this profile was accurate at the date and time of publication.

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