AdeptID announced a $3.5 Million Seed Round of venture capital for its AI and machine learning-based talent matching tech that it delivers via an API. The round was led by Zeal Capital.
AdpetID wants to do for talent matching AI what Stripe did for payments, by offering access to its algorithms and models with “a few short lines of code.” In particular AdeptID is focusing on matching the part of the workforce without college degrees to what they call “middle skill jobs.”
AdeptID isn’t the first to use the Stripe analogy for a talent-focused API product. Like the others before them, they may find the landscape trickier than what’s out in the world of payments and fintech. Stripe’s payment tech is used and integrated into the ecommerce foundation of businesses. The foundation of the talent ecosystem is made up of a highly fragmented landscape of platforms, suites, and targeted apps that impact the candidate and employee lifecycle at different points both internally and externally. Another difference is the nature of talent processes. Where Stripe manages a single transaction that is essentially the same for all products and customers, talent acquisition and talent management represent myriad workflows and transactions where matching is a supporting data point that is factored against candidates and employees that are multi-dimensional. Jobs are also multi-dimensional, but the dimensions aren’t necessarily congruent with the talent dimensions.
That’s not to say that AdeptID or the many others focused on this challenge should give up. This is a challenge that has yet to be solved. That’s due to the complexity.
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