ANDREA BREITLING

​​Client:  SignAll 

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The Problem:​

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SignAll was a computer vision technology company building a dataset of signed words and phrases, capturing variations in articulation across users. When I joined, the product existed purely as a technical capability—with no user interface or defined application.

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Their ambition was to become the world’s first sign language learning platform with real-time feedback, transforming this experimental technology into an educational product.

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• Students learning sign language often lack access to real-time feedback outside the classroom, making it difficult to know whether they are signing correctly.

• Practicing without instructor guidance can reinforce mistakes and slow progress.

• At the same time, the underlying sign-language recognition technology was entirely new—there were no established interaction patterns, learning models, or usability conventions to follow.

• Designing effective feedback required careful consideration of human factors, accessibility, and the wide variation in how individuals sign.

• The challenge was to translate experimental computer vision technology into a usable, motivating learning experience that could function in real educational environments.

 

My Role

• Built foundational understanding of Deaf culture, American Sign Language, and learning needs

• Led end-to-end product design from discovery through MVP and initial launch

• Applied human factors principles to computer vision capture and indexing of sign language

• Designed an intuitive calibration workflow for non-technical users

• Iterated rapidly on prototypes, exploring interaction models for a completely new technology with no precedents

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Outcome:

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• Productized a previously UI-less technology into a usable educational platform

• Translated experimental computer vision + sign-language recognition into a real-world learning experience

• Launched a pilot at Gallaudet University

• Enabled independent practice through real-time visual feedback outside the classroom

• Introduced a structured learn → practice → quiz model supporting multiple learning styles

• Increased engagement through gamified repetition and progress tracking

• Validated by educators as a valuable supplement to in-person instruction

Design Deliverables

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• Initial concepts, prototypes, and core UI patterns

• Gamification models to drive engagement and repetition

• Iterative design refinements and developer-ready handoffs

• User testing with Deaf and hearing participants, informing continuous improvements

• Created user documentation