Self AI - Talent OS that predicts performance, not just parses resumes
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AI-native Talent Operating System that helps companies hire and grow talent for the AI economy. Instead of relying on resumes and gut feel, Self AI embeds predictive talent data and behavioral intelligence into autonomous workflows, replacing credential-based screening with data-driven decisions that actually predict performance.
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Filliny
congrats on launching. building on the candidate side of this problem, so genuinely curious: how do you handle the training-data trap on 'predicts performance'? past performance is only observed on candidates who already got hired, which is the population that passed earlier biased filters. one common fix is calibration on a separate holdout (interviewees who didn't get hired but had observable downstream outcomes elsewhere), but that data is hard to assemble. is your dataset using something like that, or a different approach?