How “little big company” See-Mode is tackling strokes with AI, and a fresh $9.7 million in funding

See-Mode co-founders Dr Sadaf Monajemi and Dr Milad Mohammadzadeh

See-Mode co-founders Dr Sadaf Monajemi and Dr Milad Mohammadzadeh. Source: supplied.

AI-enabled stroke prediction and prevention startup See-Mode Technologies has raised US$7 million ($9.7 million) as it ramps up to its next phase of global growth.

But, in medtech, you’ve got to dream big and little at the same time, says co-founder Dr Milad Mohammadzadeh.

The funding round was led by Singapore-based MassMutual Ventures Southeast Asia, and includes repeat backing from Aussie fund Blackbird Ventures, as well as from existing investors Cocoon Capital, Entrepreneur First, and SG Innovate, plus a group of angel investors.

Blackbird co-founder and partner Niki Scevak is also joining the board of the startup.

Founded in 2017 by Mohammadzadeh and Dr Sadaf Monajemi, See-Mode uses AI and computational modelling technology to analyse medical images — such as ultrasounds and CT and MRI scans — to identify stroke risk factors.

The mission is to help doctors better predict and prevent strokes, Mohammadzadeh tells SmartCompany.

The co-founders launched the business back in 2017, after completing their PhDs in biomedical engineering.

Mohammadzadeh studied mechanics for medical applications, while Monajemi studied machine learning. So they put their heads together.

“We definitely knew that we wanted to work on something biomedical. We knew that we wanted to get into a deep technical problem around a medical application,” Mohammadzadeh says.

It was one of Singapore’s top neurologists that alerted them to the problems in stroke prediction, and set them down a path of speaking to doctors all over the world and validating the issues.

“Stroke, as a disease, has one of the highest clinical and financial impacts compared to many other diseases,” Mohammadzadeh explains.

In many countries, it’s the second leading cause of death, after heart attacks, he says. In most countries, it’s in the top three or five.

For those who suffer a stroke, it’s also often a long-term challenge.

“Many people who experience a stroke, unfortunately, end up disabled, and the ones that survive are still at high risk of repeat strokes,” Mohammadzadeh says.

“This is one of the areas that we are really hoping to make a dent in.”

“We’ve come a long way”

This latest funding follows a $1 million seed round closed in June 2018. That funding allowed the startup to prove out the technology, secure regulatory approval and launch its first product into hospitals.

It was “a massive undertaking at the time”, Mohammadzadeh says.

“We’ve come a long way.”

Now, hospitals in Australia and Singapore are running pilots with See-Mode, and the startup is gearing up to expand into the US and Europe as well.

This funding will help propel the business to the next level. The founders are looking at doubling headcount, particularly building up the sales and business development teams.

They’re also “powering through R&D”, Mohammadzadeh says.

As well as continuing its focus on stroke prevention, the startup is looking into feedback from sonographers that suggest the technology could be used in the cardiovascular space as well.

“There’s a commercial aspect to this round, as well as a pretty sizable R&D aspect.”

Dreaming big, and small

With a team of 15 people, Mohammadzadeh describes See-Mode as “a little big company”. And the founder certainly has big dreams.

“We would like to see See-Mode’s products used in as many hospitals around the world as possible,” he says.

He “absolutely” sees a future where it’s in every hospital, everywhere.

“It’s an ambitious mission for a small company, but stroke is definitely a global problem,” he adds.

“It’s just about cracking the code of better analysing these medical images … I don’t see that being disrupted by any borders and barriers.”

That said, in medtech, growth can come a little more slowly than in other sectors, Mohammadzadeh explains. You build tech to help one patient, that can end up helping 100, and then perhaps thousands, but it takes time.

“The problems are hard to solve. The evidence is hard to build, and selling to massive organisations like hospitals is slower, compared to other types of enterprise sales,” the founder notes.

“But at the end of the day, the impact on the problem can be pretty massive.”

At this point, for Mohammadzadeh and Monajemi, it’s about more than business.

“Even if the technology that we’re building helps one patient, we are happy, personally,” Mohammadzadeh says.

“It’s personal motivation that is pushing us through this.”

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