공시 • May 14
Appier Group, Inc. Provides Earnings Guidance for the Second Quarter of 2026 Appier Group, Inc. provided earnings guidance for the second quarter of 2026. For the quarter, Appier is signaling a bolstered outlook, reflecting increased confidence in its growth trajectory, with revenue projected to reach JPY 12.5 billion - JPY 12.7 billion, surpassing the initial forecast. The company also expects a significant step-up in profitability, with Second Quarter operating income projected at JPY 1.0 billion - JPY 1.2 billion, ahead of the initial forecast. This accelerated profit growth is driven by the impact of expanding operating leverage reinforced by the scalable deployment of Agentic AI solutions. 공시 • Apr 07
Appier Group, Inc. to Report Q1, 2026 Results on May 13, 2026 Appier Group, Inc. announced that they will report Q1, 2026 results on May 13, 2026 공시 • Mar 11
Appier Research Unveils Agentic AI Breakthrough: A Risk-Aware Decision Framework Appier announced new research advancing the reliability of Agentic AI systems. To expand the impact of its research and development efforts, Appier's AI research team continues to focus on frontier topics in Agentic AI and Large Language Models (LLMs), exploring forward-looking technical challenges that push the boundaries of marketing technology innovation. The research addresses a key challenge in deploying Agentic AI in enterprise environments: ensuring that autonomous AI decisions are trustworthy. The findings further strengthen Appier's technological leadership in AI while contributing practical insights for the broader Agentic AI ecosystem. As an AI-native Agentic AI-as-a-Service (AaaS) company, Appier continues to translate cutting-edge research into enterprise-ready methodologies and product capabilities. This study specifically addresses two major enterprise concerns: AI hallucinations and decision reliability. To tackle this challenge, the research introduces a Risk-Aware Decision-Making framework that converts LLM decisions across varying risk conditions into quantifiable metrics, providing a stronger governance foundation for enterprise AI deployment. Turning Risk-Aware Strategies into Quantifiable Metrics: Traditional LLM evaluations focus primarily on whether an answer is correct. In enterprise environments, however, the cost of being wrong and the value of refusing to answer differ significantly. The study introduces structured risk parameters—including rewards for correct answers, penalties for incorrect responses, and costs for refusal—to simulate different risk scenarios. Under this framework, models must evaluate their capability, confidence level, and risk conditions before deciding whether to answer, refuse, or guess. Decision quality is then measured by whether the model maximizes expected reward, providing a more realistic assessment of strategic decision-making; Key Finding: Strategic Imbalance in Existing Models: Using the Risk-Aware Decision-Making framework, the research finds that many leading LLMs display strategic imbalance across risk scenarios. In high-risk settings, models often over-guess despite potential negative consequences. In low-risk scenarios, they may become overly conservative and refuse to answer too frequently. This inconsistency limits both the autonomy and safety of AI systems in enterprise environments. The study suggests the issue is not purely knowledge-related but stems from the model's difficulty in integrating multiple capabilities into a stable decision strategy; Skill Decomposition Enables More Optimal Decisions: To address this challenge, the research proposes a Skill Decomposition approach, breaking decision-making into three steps: Task Execution — solving the task to generate an initial answer; Confidence Estimation — evaluating confidence in that answer; Expected-Value Reasoning — reasoning about outcomes under risk conditions. 공시 • Dec 24
Appier Group, Inc. to Report Q4, 2025 Results on Feb 13, 2026 Appier Group, Inc. announced that they will report Q4, 2025 results on Feb 13, 2026 공시 • Sep 23
Appier Announces Full Product Line Infused with Agentic AI, Ushering in a New Era of ROI Driven Marketing Solutions Appier announced the infusion of Agentic AI across its entire product portfolio and the launch of eight purpose built AI Agents. Designed to help advertisers and marketers deliver predictable ROI, the new suite redefines how data and AI power every stage of the customer journey. Unlike one off task automation, Appier's Agents combine predictive insights with industry best practices to coordinate end to end actions, accelerating time to ROI and driving measurable business impact. Built on its vision of "One Data. One Experience. One Agentic World,"Appier outlined the roadmap for its AI Agents. The new framework reimagines how data is collected and activated, instantly connecting, unifying and operationalizing fragmented datasets to surface real time market shifts and enable autonomous, adaptive and intelligent omnichannel marketing. With AI Agents, brands gain a 24/7 autonomous marketing partner that supports teams from strategy through execution, helping them overcome legacy constraints and make clearer, more confident decisions. Appier's eight upgraded AI Agents span three product lines: Advertising Cloud (Coding Agent, Director Agent, ROI Agent), Personalization Cloud (Sales Agent, Campaign Agent, Service Agent), and Data Cloud (Audience Agent, Insight Agent). Built with deep industry expertise, these Agents train on each brand's proprietary knowledge to create predictive models that turn data into predictable revenue and returns. Paired with 24/7 self learning and automated optimization, they deliver hyper personalized engagement at scale. As these Agents interconnect, enterprises can establish seamless agentic workflows that further improve precision and efficiency while simplifying business outcomes. 
