Sana Labs raises $18 million to upskill workers remotely with machine learning - News AKMI

Sana Labs, a startup that’s using machine learning to personalize training courses for professionals, has raised $18 million in a series A round of funding led by EQT Ventures.

As with just about all facets of life during the pandemic, online training and education has surged over the past year, with schools, colleges, and universities forced to embrace (socially) distanced learning. The same is just as true in the corporate sphere, with companies not only having to transition to remote work but also figure out how to coach and upskill their workforce from afar.

According to World Economic Forum (WEF), more than 40% of core skills needed to perform existing jobs are expected to change by 2022 as the so-called “fourth industrial revolution” transforms industries. And this is essentially where Sana Labs is setting out to help with an “adaptive learning platform” that automatically identifies where skill gaps exist and tailors a program accordingly.

Customers use the Sana Labs authoring tool to upload the content and design the courses, upon which Sana Labs applies its ML.

“Automated learning assistant technology understands where misalignments exist between learning and the individuals’ skills gap,” Sana Labs CEO Joel Hellermark told VentureBeat. “With adaptive assessment, learning, and review, the learning assistant personalizes the path to the individual needs of the learner — surfacing just what they need, right when they need it.”

Founded out of Stockholm, Sweden, in 2016, Sana Labs claims customers across finance, pharmaceutical, and health care including Novartis, PepsiCo, and Mount Sinai. During the pandemic, Sana Labs said it was adopted by 2,000 hospitals which used the platform to upskill more than 80,000 health care workers on the treatment and prevention of COVID-19, by first determining the existing knowledge of each nurse and then automatically generating a program to bridge the gaps.

One of the key challenges of this approach is that a lack of human coaching and prompts, as you would perhaps get in a classroom setting, is difficult to recreate in this kind of platform. For example, a teacher could see where an individual is at, how they’re progressing, and “encourage” them to finish an assignment. To replicate this, Sana Labs uses “nudging,” which are what it calls “scientifically-based behavioral and pedagogical interventions.”

“Smart nudging is another component which leverages behavior data to provide tiny interventions to increase the rate of course completion,” Hellermark added. “Using AI allows actionable insights to be personalized and delivered in real time to identify patterns in learners data and provide insights.”

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