Since its founding in 2012, Flitto has built and operated a platform capable of collecting, refining, and constructing language datasets across text, speech, image, and multimodal formats. While the company initially focused on building relatively simple parallel corpora and single-language speech datasets, it has continuously advanced its platform to meet increasingly complex data needs, ranging from university-level STEM text and long-form translation datasets to speech datasets reflecting dialectal variation and prosodic nuance. This accumulated expertise in data construction has been recognized across both industry and public sectors, forming a core foundation of Flitto’s technological credibility.
The next stage of Flitto’s technological evolution is hyper-personalization. Hyper-personalization refers to an advanced level of AI that provides communication optimized for each individual, capturing a user’s linguistic habits, pronunciation patterns, preferred spellings, stylistic tendencies, and domain-specific knowledge. (Source: How Generative AI Is Driving Hyperpersonalization)
Even a single name can produce multiple legitimate variations, such as:
• LEE JUNG SU
• LEE JEONG SOO
Traditional pattern-based AI systems are unable to interpret these differences as intentional preferences. To address this, Flitto has developed a structure that allows users to directly register or modify their preferred spellings, pronunciations, keywords, and styles as part of their personal dataset. The model references this information as a priority, producing outputs that reflect the user’s linguistic identity and preferences.
This hyper-personalization framework has already been validated through Flitto’s real-time translation services. Words that were previously unrecognized in conference environments or instances of mistranslation are continuously converted into new datasets and reintegrated into the learning pipeline. This iterative improvement process enhances overall STT and NMT performance while simultaneously reinforcing the hyper-personalization engine that adapts to each individual user.
As we move toward the era of AGI, general-purpose models will be required to demonstrate increasingly sophisticated comprehension, reasoning, and contextual transfer. The ability to capture a user’s linguistic rhythm, cultural context, and communicative patterns will become a defining competitive advantage. This is why Flitto positions hyper-personalization not as an optional feature but as a core component of its technological identity, structuring AI systems to evolve from simply “providing correct answers” to “expressing and understanding in the user’s own way.”
Ultimately, language is the most human form of data, an accumulation of culture, emotion, and thought. Flitto views language not as an object of computation but as a foundation for human understanding. Guided by principles of data quality, linguistic diversity, and fairness, Flitto has built a global language infrastructure that ensures consistent communication experiences for users worldwide.
As Physical AI and AGI continue to advance, AI systems will require richer datasets and more complex interaction patterns. With its deep expertise in data construction and its hyper-personalization engine, Flitto is committed to shaping an AI future that is more accurate, more equitable, and more human-centered.