Nota AI Lists on KOSDAQ, Expands Globally in AI Model Optimization

ByRicardo
  • Successfully listed on KOSDAQ with distinctive competitiveness for AI lightweighting and optimization expertise
  • Driving fast annual income progress by way of collaborations with international leaders together with NVIDIA, Samsung Electronics, and Qualcomm
  • Focusing post-IPO efforts on creating a next-generation optimization platform and increasing international markets

NAVER D2SF–backed Nota AI, an organization specializing in AI mannequin compression and optimization applied sciences, introduced its itemizing on the KOSDAQ market as of November. NAVER D2SF, NAVER’s company enterprise capital (CVC), made an early funding in Nota AI shortly after its founding in 2015 and has since constantly supported the corporate’s progress. Through its KOSDAQ itemizing, Nota AI has as soon as once more demonstrated the expansion potential of its distinctive AI lightweighting and optimization applied sciences.

Nota AI has secured technological competitiveness by way of its independently developed AI mannequin optimization platform, ‘NetsPresso®,’ and its on-device AI options. AI lightweighting and optimization expertise is gaining vital international consideration because it successfully reduces the burden of surging adoption and operational prices related to high-performance AI fashions, whose current emergence has elevated enterprises’ expenditure on AI implementation.

AI mannequin optimization expertise of Nota AI is at present being superior by way of collaboration with international trade leaders, together with NVIDIA, Samsung Electronics, Qualcomm, Arm, and Sony. This expertise is more and more acknowledged as a core functionality, notably with the expansion of Physical AI sectors resembling autonomous driving and robotics. Furthermore, Nota AI was named one of many ‘2025 Global Innovative AI Startups 100’ by CB Insights this 12 months.

Furthermore, Nota AI continues to develop the applicability of AI throughout numerous industries together with industrial security, visitors management, selective surveillance, retail, and healthcare by way of ‘Nota Vision Agent(NVA),’ a video monitoring answer that applies a generative AI-based Vision-Language Model(VLM) to on-device environments.

Nota AI is focusing its post-IPO efforts on enhancing its AI optimization expertise competitiveness and increasing its goal markets the place Edge AI might be utilized. The firm plans to strengthen its market place by way of proactive gross sales and advertising concentrating on international semiconductor corporations and system producers in key markets such because the United States, Europe, and the Middle East, and can closely make investments in creating a next-generation platform able to optimizing an excellent wider number of AI fashions. In explicit, strategic collaborations with international embedded trade leaders are anticipated to extend market share and drive gross sales progress in high-growth sectors like protection and aerospace.

Nota AI has secured a broad base of world purchasers, together with Fortune Global 500 corporations and the UAE’s Dubai Roads and Transport Authority(RTA), driving fast annual income progress. The firm achieved greater than double its income, rising from roughly $2.52 million in 2023 to roughly $5.89 million in 2024. Nota AI is concentrating on roughly $10.17 million in income for 2025 and goals to attain a turnaround to profitability by 2027.

Myungsu Chae, CEO of Nota AI, stated, “This IPO is an important strategic determination that goes past mere capital procurement, serving as a substitute as a definitive alternative to earn the belief of the worldwide market and set up a sturdy basis for exponential future progress. We will proceed to steer innovation throughout industries by way of our AI optimization applied sciences and understand the imaginative and prescient of ‘AI Everywhere,’ enabling clever methods to function seamlessly throughout numerous environments.”

The submit Nota AI Lists on KOSDAQ, Expands Globally in AI Model Optimization first appeared on AI-Tech Park.

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