Finding the right learning platform can be difficult, especially as companies look to upskill and reskill their talent to meet demand for certain technological capabilities, like data science, machine learning and artificial intelligence roles.
Workera.ai’s approach is to personalize learning plans with targeted resources — both technical and nontechnical roles — based on the current level of a person’s proficiency, thereby closing the skills gap.
The Palo Alto-based company secured $16 million in Series A funding, led by New Enterprise Associates, and including existing investors Owl Ventures and AI Fund, as well as individual investors in the AI field like Richard Socher, Pieter Abbeel, Lake Dai and Mehran Sahami.
Kian Katanforoosh, Workera’s co-founder and CEO, says not every team is structured or feels supported in their learning journey, so the company comes at the solution from several angles with an assessment on mentorship, where the employee wants to go in their career and what skills they need for that, and then Workera will connect those dots from where the employee is in their skillset to where they want to go. Its library has more than 3,000 micro-skills and personalized learning plans.
“It is what we call precision upskilling,” he told TechCrunch. “The skills data then can go to the organization to determine who are the people that can work together best and have a complementary skill set.”
Workera was founded in 2020 by Katanforoosh and James Lee, COO, after working with Andrew Ng, Coursera co-founder and Workera’s chairman. When Lee first connected with Katanforoosh, he knew the company would be able to solve the problem around content and basic fundamentals of upskilling.
It raised a $5 million seed round last October to give the company a total of $21 million raised to date. This latest round was driven by the company’s go-to-market strategy and customer traction after having acquired over 30 customers in 12 countries.
Over the past few quarters, the company began working with Fortune 500 companies, including Accenture and Siemens Energy, across industries like professional services, medical devices and energy, Lee said. As spending on AI skills is expected to exceed $79 billion by 2022, he says Workera will assist in closing the gap.
“We are seeing a need to measure skills,” he added. “The size of the engagements are a sign as is the interest for tech and non-tech teams to develop AI literacy, which is a more pressing need.”
As a result, it was time to increase the engineering and science teams, Katanforoosh said. He plans to use the new funding to invest in more talent in those areas and to build out new products. In addition, there are a lot of natural language processes going on behind the scenes, and he wants the company to better understand it at a granular level so that the company can assess people more precisely.
Carmen Chang, general partner and head of Asia at NEA, said she is a limited partner in Ng’s AI fund and in Coursera, and has looked at a lot of his companies.
She said she is “very excited” to lead the round and about Workera’s concept. The company has a good understanding of the employee skill set, and with the tailored learning program, will be able to grow with company needs, Chang added.
“You can go out and hire anyone, but investing in the people that you have, educating and training them, will give you a look at the totality of your employees,” Chang said. “Workera is able to go in and test with AI and machine learning and map out the skill sets within a company so they will be able to know what they have, and that is valuable, especially in this environment.”
