
Samsung Electronics AI Bixby
AI Assistant
In commercial AI assistants, how the system speaks is a core design decision, not a surface detail.
dda defined Bixby’s persona and conversational principles, and designed operational quality standards through UX writing and language data architecture—supporting consistent behavior and sustainable operation at scale.
- Persona design defining who Bixby should feel like to users, establishing a clear, human-legible identity that guides tone, behavior, and interaction across the assistant.
- Standardizing tone, voice, and explanatory style so the assistant communicates with clarity and consistency across all contexts and situations.
- Designing conversation flows and sentence structures that are intuitive for users, ensuring clarity, predictability, and ease of understanding throughout the interaction.
- Structuring language data with model training and long-term improvement in mind, enabling continuous learning while preserving consistency, judgment criteria, and operational quality.
- Establishing operational standards that preserve quality across multilingual environments, ensuring consistency, judgment alignment, and sustainable performance at scale.
dda defined Bixby’s persona and conversational principles, and designed operational quality standards through UX writing and language data architecture—supporting consistent behavior and sustainable operation at scale.
- Persona design defining who Bixby should feel like to users, establishing a clear, human-legible identity that guides tone, behavior, and interaction across the assistant.
- Standardizing tone, voice, and explanatory style so the assistant communicates with clarity and consistency across all contexts and situations.
- Designing conversation flows and sentence structures that are intuitive for users, ensuring clarity, predictability, and ease of understanding throughout the interaction.
- Structuring language data with model training and long-term improvement in mind, enabling continuous learning while preserving consistency, judgment criteria, and operational quality.
- Establishing operational standards that preserve quality across multilingual environments, ensuring consistency, judgment alignment, and sustainable performance at scale.
Since 2016