View Future GrowthNota 과거 순이익 실적과거 기준 점검 0/6Nota은 연평균 33.1%의 비율로 수입이 증가해 온 반면, Software 산업은 연평균 7.9%의 비율로 증가했습니다. 매출은 연평균 55.3%의 비율로 증가했습니다.핵심 정보33.08%순이익 성장률71.21%주당순이익(EPS) 성장률Software 산업 성장률14.56%매출 성장률55.27%자기자본이익률-60.57%순이익률-126.93%최근 순이익 업데이트31 Dec 2025최근 과거 실적 업데이트업데이트 없음모든 업데이트 보기Recent updates공지 • Mar 17Nota Inc., Annual General Meeting, Mar 31, 2026Nota Inc., Annual General Meeting, Mar 31, 2026, at 10:00 Tokyo Standard Time. Location: conference room, 1, expo-ro, yuseong-gu, daejeon South Korea공지 • Mar 10Nota AI Showcases End-To-End On-Device AI At Embedded World 2026Nota AI, an AI optimization technology company, announced that it will participate in Embedded World 2026, taking place March 10-12 in Nuremberg, Germany. At the event, the company will present the full lifecycle of on-device AI-from model optimization to deployment in real-world industrial environments. Nota AI will showcase how AI models are optimized through NetsPresso® and deployed across a wide range of global hardware platforms before being implemented in real industrial environments. Nota AI will demonstrate how semiconductor companies can rapidly optimize high-performance AI models for their chips using its AI model optimization platform, NetsPresso®. The company has accumulated extensive expertise in lightweighting and optimizing AI models—from small language models (SLMs) to large language models (LLMs) and vision-language models (VLMs). To date, Nota AI has successfully compressed more than 40 AI models while maintaining performance and has deployed its optimization technologies across over 100 hardware devices. The company recently supplied AI optimization technology for Samsung Electronics' Exynos 2600, where the technology serves as a core component enabling mobile on-device AI capabilities. Nota AI has also maintained ongoing technology collaborations with global semiconductor companies including Qualcomm and Arm. At Embedded World, the company will present live demonstrations showing both computer vision models and large language models running in real time on these hardware platforms, highlighting AI performance in edge environments. Nota AI will also showcase a Device Farm, featuring a collection of hardware platforms optimized by the company over the past decade. Visitors will be able to explore a range of chipsets from major global semiconductor companies running AI models optimized with Nota AI's technology, demonstrating the company's experience in optimizing more than 100 hardware platforms over the past ten years. Nota AI will introduce real-world solutions that combine AI models with hardware optimization in on-device environments. Through its video analytics solution NVA (Nota Vision Agent), Nota AI has delivered technologies across industries such as safety monitoring, security, and smart city operations in collaboration with global partners including NVIDIA. At the booth, the company will demonstrate real deployment cases including selective video monitoring, intelligent transportation systems (ITS), and industrial safety monitoring. Nota AI will also present its latest research achievements recently accepted at ICLR 2026 and the AAAI 2026 Foundation Model Workshop. Both studies focus on improving the efficiency and reliability of vision-language models (VLMs), highlighting Nota AI's technological capabilities across the broader physical AI landscape-from vision-language models to vision-language-action (VLA) systems. During the exhibition, Tae-Ho Kim, CTO & Co-Founder of Nota AI, will host mini sessions at the booth to present the company's AI lightweighting and optimization strategies and share real-world cases of applying Nota AI technologies to global semiconductor platforms. Nota AI will offer complimentary Embedded World visitor passes to attendees who pre-register through the company's official website and visit the Nota booth (Hall 5, Booth 5-422).공지 • Mar 06Nota AI Announces Proprietary Quantization Technology For Upstage Solar LLMNota AI, an AI optimization technology company behind the Nota AI brand, announced that it has developed a next-generation quantization technology that significantly compresses the size of Solar, a high-performance large language model (LLM) developed by Upstage, while maintaining high accuracy. The breakthrough reduces inference costs and improves processing speed without sacrificing performance. The development was carried out as part of the Sovereign AI Foundation Model Project led by South Korea's Ministry of Science and ICT. By applying Nota AI's lightweighting and optimization technologies to Solar Open 100B, the company significantly improved memory efficiency while preserving model performance. The achievement lowers the memory requirements of the 100B-parameter model while maintaining its capabilities, enabling more practical deployment of Korean AI foundation models in physical AI environments such as mobility and robotics. The newly developed technology focuses on addressing technical challenges associated with the Mixture of Experts (MoE) architecture, which is rapidly gaining adoption in next-generation LLMs. Conventional quantization methods typically compress the entire model uniformly without considering the distinct characteristics of individual expert models. To overcome this limitation, Nota AI developed a proprietary algorithm optimized for MoE architectures, called Nota AI MoE Quantization. The approach is designed to minimize quantization distortion during the inference process of MoE models. Unlike conventional methods that uniformly reduce precision across all operations, Nota AI's algorithm selectively preserves precision in critical components while compressing less sensitive parts of the model. This enables effective model compression while minimizing performance loss. Applying the technology to the Solar 100B model yielded significant improvements compared with conventional quantization methods. Nota AI successfully reduced Solar's memory usage from 191.2GB to 51.9GB, representing a 72.8% reduction. At the same time, the model maintained performance levels comparable to the original version, achieving a Perplexity (PPL) score of 6.81, close to the baseline model's 6.06. In contrast, some generic quantization approaches resulted in performance degradation exceeding fivefold. Nota AI has filed a patent application for the technology to strengthen its intellectual property portfolio. While conventional quantization techniques often sacrifice model performance to reduce memory usage, Nota AI's technology demonstrates that it is possible to maintain performance while delivering AI services faster and to more users on limited GPU infrastructure. As a result, enterprises can deploy large-scale LLMs more easily on their own devices—models that were previously difficult to implement due to hardware constraints. The significant reduction in Solar 100B's memory footprint while preserving performance also creates new opportunities for deploying high-performance AI in real-world on-device environments, including robotics and automotive systems. Additionally, the technology enables organizations facing limited access to high-end GPU infrastructure to serve more users on the same hardware, directly contributing to lower operational costs.분석 기사 • Feb 03Health Check: How Prudently Does Nota (KOSDAQ:486990) Use Debt?David Iben put it well when he said, 'Volatility is not a risk we care about. What we care about is avoiding the...매출 및 비용 세부 내역Nota가 돈을 벌고 사용하는 방법. 최근 발표된 LTM 실적 기준.순이익 및 매출 추이KOSDAQ:A486990 매출, 비용 및 순이익 (KRW Millions)날짜매출순이익일반관리비연구개발비31 Dec 2513,101-16,63025,74365630 Sep 2510,223-25,72821,89273530 Jun 258,817-25,44418,95197031 Mar 258,627-25,14818,16796431 Dec 248,437-24,85217,38395731 Dec 233,581-13,13511,7732,002양질의 수익: A486990 은(는) 현재 수익성이 없습니다.이익 마진 증가: A486990는 현재 수익성이 없습니다.잉여현금흐름 대비 순이익 분석과거 순이익 성장 분석수익추이: 지난 5년 동안 A486990의 연간 수익 성장률이 양(+)이었는지 판단하기에 데이터가 부족합니다.성장 가속화: 현재 수익성이 없어 지난 1년간 A486990의 수익 성장률을 5년 평균과 비교할 수 없습니다.수익 대 산업: A486990은 수익성이 없어 지난 해 수익 성장률을 Software 업계(3.6%)와 비교하기 어렵습니다.자기자본이익률높은 ROE: A486990는 현재 수익성이 없으므로 자본 수익률이 음수(-60.57%)입니다.총자산이익률투하자본수익률우수한 과거 실적 기업을 찾아보세요7D1Y7D1Y7D1YSoftware 산업에서 과거 실적이 우수한 기업.View Financial Health기업 분석 및 재무 데이터 상태데이터최종 업데이트 (UTC 시간)기업 분석2026/05/07 23:59종가2026/05/07 00:00수익2025/12/31연간 수익2025/12/31데이터 소스당사의 기업 분석에 사용되는 데이터는 S&P Global Market Intelligence LLC에서 제공됩니다. 아래 데이터는 이 보고서를 생성하기 위해 분석 모델에서 사용됩니다. 데이터는 정규화되므로 소스가 제공된 후 지연이 발생할 수 있습니다.패키지데이터기간미국 소스 예시 *기업 재무제표10년손익계산서현금흐름표대차대조표SEC 양식 10-KSEC 양식 10-Q분석가 컨센서스 추정치+3년재무 예측분석가 목표주가분석가 리서치 보고서Blue Matrix시장 가격30년주가배당, 분할 및 기타 조치ICE 시장 데이터SEC 양식 S-1지분 구조10년주요 주주내부자 거래SEC 양식 4SEC 양식 13D경영진10년리더십 팀이사회SEC 양식 10-KSEC 양식 DEF 14A주요 개발10년회사 공시SEC 양식 8-K* 미국 증권에 대한 예시이며, 비(非)미국 증권에는 해당 국가의 규제 서식 및 자료원을 사용합니다.별도로 명시되지 않는 한 모든 재무 데이터는 연간 기간을 기준으로 하지만 분기별로 업데이트됩니다. 이를 TTM(최근 12개월) 또는 LTM(지난 12개월) 데이터라고 합니다. 자세히 알아보기.분석 모델 및 스노우플레이크이 보고서를 생성하는 데 사용된 분석 모델에 대한 자세한 내용은 당사의 Github 페이지에서 확인하실 수 있습니다. 또한 보고서 활용 방법에 대한 가이드와 YouTube 튜토리얼도 제공합니다.Simply Wall St 분석 모델을 설계하고 구축한 세계적 수준의 팀에 대해 알아보세요.산업 및 섹터 지표산업 및 섹터 지표는 Simply Wall St가 6시간마다 계산하며, 프로세스에 대한 자세한 내용은 Github에서 확인할 수 있습니다.분석가 소스Nota Inc.는 3명의 분석가가 다루고 있습니다. 이 중 3명의 분석가가 우리 보고서에 입력 데이터로 사용되는 매출 또는 수익 추정치를 제출했습니다. 분석가의 제출 자료는 하루 종일 업데이트됩니다.분석가기관Eun Jung ShinDB Financial Investment Co. Ltd.Jongsun ParkEugene Investment & Securities Co Ltd.Jun Ki BaekNH Investment & Securities Co., Ltd.
공지 • Mar 17Nota Inc., Annual General Meeting, Mar 31, 2026Nota Inc., Annual General Meeting, Mar 31, 2026, at 10:00 Tokyo Standard Time. Location: conference room, 1, expo-ro, yuseong-gu, daejeon South Korea
공지 • Mar 10Nota AI Showcases End-To-End On-Device AI At Embedded World 2026Nota AI, an AI optimization technology company, announced that it will participate in Embedded World 2026, taking place March 10-12 in Nuremberg, Germany. At the event, the company will present the full lifecycle of on-device AI-from model optimization to deployment in real-world industrial environments. Nota AI will showcase how AI models are optimized through NetsPresso® and deployed across a wide range of global hardware platforms before being implemented in real industrial environments. Nota AI will demonstrate how semiconductor companies can rapidly optimize high-performance AI models for their chips using its AI model optimization platform, NetsPresso®. The company has accumulated extensive expertise in lightweighting and optimizing AI models—from small language models (SLMs) to large language models (LLMs) and vision-language models (VLMs). To date, Nota AI has successfully compressed more than 40 AI models while maintaining performance and has deployed its optimization technologies across over 100 hardware devices. The company recently supplied AI optimization technology for Samsung Electronics' Exynos 2600, where the technology serves as a core component enabling mobile on-device AI capabilities. Nota AI has also maintained ongoing technology collaborations with global semiconductor companies including Qualcomm and Arm. At Embedded World, the company will present live demonstrations showing both computer vision models and large language models running in real time on these hardware platforms, highlighting AI performance in edge environments. Nota AI will also showcase a Device Farm, featuring a collection of hardware platforms optimized by the company over the past decade. Visitors will be able to explore a range of chipsets from major global semiconductor companies running AI models optimized with Nota AI's technology, demonstrating the company's experience in optimizing more than 100 hardware platforms over the past ten years. Nota AI will introduce real-world solutions that combine AI models with hardware optimization in on-device environments. Through its video analytics solution NVA (Nota Vision Agent), Nota AI has delivered technologies across industries such as safety monitoring, security, and smart city operations in collaboration with global partners including NVIDIA. At the booth, the company will demonstrate real deployment cases including selective video monitoring, intelligent transportation systems (ITS), and industrial safety monitoring. Nota AI will also present its latest research achievements recently accepted at ICLR 2026 and the AAAI 2026 Foundation Model Workshop. Both studies focus on improving the efficiency and reliability of vision-language models (VLMs), highlighting Nota AI's technological capabilities across the broader physical AI landscape-from vision-language models to vision-language-action (VLA) systems. During the exhibition, Tae-Ho Kim, CTO & Co-Founder of Nota AI, will host mini sessions at the booth to present the company's AI lightweighting and optimization strategies and share real-world cases of applying Nota AI technologies to global semiconductor platforms. Nota AI will offer complimentary Embedded World visitor passes to attendees who pre-register through the company's official website and visit the Nota booth (Hall 5, Booth 5-422).
공지 • Mar 06Nota AI Announces Proprietary Quantization Technology For Upstage Solar LLMNota AI, an AI optimization technology company behind the Nota AI brand, announced that it has developed a next-generation quantization technology that significantly compresses the size of Solar, a high-performance large language model (LLM) developed by Upstage, while maintaining high accuracy. The breakthrough reduces inference costs and improves processing speed without sacrificing performance. The development was carried out as part of the Sovereign AI Foundation Model Project led by South Korea's Ministry of Science and ICT. By applying Nota AI's lightweighting and optimization technologies to Solar Open 100B, the company significantly improved memory efficiency while preserving model performance. The achievement lowers the memory requirements of the 100B-parameter model while maintaining its capabilities, enabling more practical deployment of Korean AI foundation models in physical AI environments such as mobility and robotics. The newly developed technology focuses on addressing technical challenges associated with the Mixture of Experts (MoE) architecture, which is rapidly gaining adoption in next-generation LLMs. Conventional quantization methods typically compress the entire model uniformly without considering the distinct characteristics of individual expert models. To overcome this limitation, Nota AI developed a proprietary algorithm optimized for MoE architectures, called Nota AI MoE Quantization. The approach is designed to minimize quantization distortion during the inference process of MoE models. Unlike conventional methods that uniformly reduce precision across all operations, Nota AI's algorithm selectively preserves precision in critical components while compressing less sensitive parts of the model. This enables effective model compression while minimizing performance loss. Applying the technology to the Solar 100B model yielded significant improvements compared with conventional quantization methods. Nota AI successfully reduced Solar's memory usage from 191.2GB to 51.9GB, representing a 72.8% reduction. At the same time, the model maintained performance levels comparable to the original version, achieving a Perplexity (PPL) score of 6.81, close to the baseline model's 6.06. In contrast, some generic quantization approaches resulted in performance degradation exceeding fivefold. Nota AI has filed a patent application for the technology to strengthen its intellectual property portfolio. While conventional quantization techniques often sacrifice model performance to reduce memory usage, Nota AI's technology demonstrates that it is possible to maintain performance while delivering AI services faster and to more users on limited GPU infrastructure. As a result, enterprises can deploy large-scale LLMs more easily on their own devices—models that were previously difficult to implement due to hardware constraints. The significant reduction in Solar 100B's memory footprint while preserving performance also creates new opportunities for deploying high-performance AI in real-world on-device environments, including robotics and automotive systems. Additionally, the technology enables organizations facing limited access to high-end GPU infrastructure to serve more users on the same hardware, directly contributing to lower operational costs.
분석 기사 • Feb 03Health Check: How Prudently Does Nota (KOSDAQ:486990) Use Debt?David Iben put it well when he said, 'Volatility is not a risk we care about. What we care about is avoiding the...