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Multimodal AI

See the skills and the personality candidates bring to the table

Multimodal AI takes into account multiple modes of communication and how they interact with one another to create semiotic meaning. This allows our AI to draw insightful conclusions to assessments done by your candidates in job-like simulations.

Used as a way to understand not only the written meaning of discourse but also other elements that contribute to it, our AI makes it possible to base your hiring decision on real data - according to the study of 4 modalities : Paraverbal (tone of voice), Oral, Written, Non verbal.

Each modality is linked to a skills library - this allows our AI to run tests by combining all these factors (behavior and skills) together to get results.

Ask for our detailed AI & Machine Learning Models

Oral segmentation topic segmentation and content analysis

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Speech rate speed, quality and more

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Vocal characteristics voice tremor, range and more

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Face semantic analyses

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Eye tracking movement, intensity of movement

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Heatmap cognitive reasoning and its intensity

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Voice semantic analyses

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Turmoil analyses control with standard deviation and variation of coefficients, calculation of derivatives

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Perceived inspirations control with standard deviation and variation of coefficients, calculation of derivatives

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Heart rate control with standard deviation and variation of coefficients, calculation of derivatives

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sweeeft is the only solution to introducing AI machine learning to Human Resources, with 5+ years of R&D and current research and publications across CNRS, Liris, icar, and LIG labs.