Aankondiging • 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.

Aankondiging • Dec 14

Appier launches AIRIS, the next-gen AI-powered CDP leveraging first-party data to activate MarTech applications

Appier announced the launch of AIRIS, the next-generation AI-powered CDP to support brands and marketers to achieve the fastest time-to-insight with smarter decision-making and execution by leveraging its advanced AI and Machine Learning technologies. This launch comes following its acquisition of Woopra in October and is a combination of AIXON's advanced user-centric predictive AI capabilities with Woopra's superior data analytics and intuitive data visualization to help enterprises turn data to insight, and insights to action and results. The name AIRIS is derived from the word "iris", which strongly reflects its visualization features that will empower enterprises to identify customers precisely and generate timely predictive insights. AIRIS meets the current pain points of shorter time-to-insights and prediction requests that enterprises need to maximize their campaign ROIs to better respond to market challenges. Appier completing the integration just two months after the Woopra acquisition is a strong demonstration of its position as a leading AI SaaS company. AIRIS is available across Asia Pacific in English, Japanese, and Traditional Chinese with flexible and scalable pricing packages to suit enterprises of all sizes. Fragmented and missing data are some of the key reasons driving the higher costs of personalization for brands. What enterprises care about the most is usually the hardest to predict. With the next-generation CDP AIRIS, enterprises can integrate and synchronize customer data via one-click integrations and analyze every touch point throughout the customers' journeys to gain more insights. With its AI-powered prediction capability, enterprises can now create more campaigns that have a higher likelihood of being received well by customers, unleashing the full benefits of a CDP to maximize business value and impact. Brands and marketers stand to benefit from AIRIS in the following five ways: 1. Increase the value of first-party data and empower data storytelling: In response to several restrictions around the use of third-party data, AIRIS can seamlessly integrate various data sources, including existing cloud databases, online and offline sales data, and user data across web, app, messenger, and more than 50 external platforms to establish user-centric and comprehensive 360-degree customer views. Brands will be able to tell stories with data by visualizing customers' purchase intent, preferences, and decision-making tendencies. With the inferred data insights and AI extrapolations, enterprises will now be able to tailor more effective and personalized marketing strategies. 2. Grant a higher level of autonomy and flexibility for marketers:Without data science capabilities, it is hard for marketers to quickly develop marketing strategies and directions. AIRIS is equipped with several marketer-friendly features, such as defining user attributes in one-click, plug-and-play set-up, and low-code/no-code interface so that marketers can easily gain insights to make decisions and plan activities without the help of IT, data scientists, or manual data analysis. This advantage is even more crucial in the current post-Covid era, as it can solve marketers' challenges fundamentally to help them cope with the fast-changing market environment. 3. Data visualization is like a gold mine of insights: Through built-in user-centric and intuitive analysis templates, AIRIS can visualize the impact on the user at every touchpoint, supporting marketers to analyze long-term cohort behaviors through timeframe, segment, retention, and churn rate analysis, and find out the correlations and insights. For example, marketers can analyze campaign performance and its correlations and uplift cues by browsing "how many users are repeatedly making purchases after they sign up", observing "the changes in monthly revenue after adopting a specific coupon delivery campaign", and analyzing "users' revisit, interaction, and purchase behavior for several months after sign up". 4. Preview and predict performance before investment to maximize ROI: AIRIS can tag onsite visitors with more than 500 predictive user attributes in real-time, allowing marketers to quickly tailor engagement and prediction models through an automated Machine Learning platform to create more campaigns that are received well by customers. With AIRIS, marketers can also predict before investment by reviewing the correlations between marketing activity and sales growth, as well as getting to know why a customer stopped its journey on a specific channel. By predicting users who have higher chances to purchase or with a higher chance to churn, marketers can retarget high-value customers and customize product recommendations or coupon delivery to further enhance campaign performance and optimize their return on investment. 5. Responding to data privacy regulations to ensure user data security: Growing concerns about data privacy from customers and regulations regarding data privacy have set up a higher compliance standard for enterprises. Enterprises are now being requested to review and delete user data when users ask for the "Right to be forgotten (RTBF)". Adopting AIRIS can enable enterprises to manage users' cookie consent easily and maximize the value of data while respecting users' data privacy for further analysis and campaign usage. Appier has always been committed to protecting every client's and their customer's data and has also been transparent in how data is being collected, utilized, and shared. Ensuring user data security while fulfilling the needs of data processing for enterprises of all sizes is of the utmost importance for Appier. AIRIS's powerful and highly customizable features can simplify routine marketing tasks. Coupled with Appier's strong AI-powered prediction and analytics capability, AIRIS can further enrich data or bridge gaps in marketing campaigns. Marketers can now focus on tasks that matter the most and stay aligned with the organization's strategic goals while paying close attention to their customer's needs and experiences to truly empower first-party data-centric solutions and activate the power of MarTech applications.

Percentage CEO-salaris	n/a
Dienstverband CEO	7.3yrs
Eigendom CEO	1.4%
Management gemiddelde ambtstermijn	geen gegevens
Gemiddelde ambtstermijn bestuur	7yrs

Naam	Positie	Tenure	Compensatie	Eigendom
Chih-Han Yu	Co-Founder	7.3yrs	geen gegevens	1.38% ¥ 1.4b
Wan-Ling Lee	Co-Founder	7.3yrs	geen gegevens	1.63% ¥ 1.7b
Chia-Yung Su	Co-Founder	7.3yrs	geen gegevens	3.88% ¥ 3.9b
Jing-Ting Tu	Senior VP of Global Sales & Director	6.8yrs	geen gegevens	0.14% ¥ 141.0m
Ching-Hua Ho	Independent Outside Director	4.2yrs	geen gegevens	geen gegevens
Takashi Motomura	Independent Outside Director	6.8yrs	geen gegevens	geen gegevens
Lee-Feng Chien	Independent Outside Director	7.3yrs	geen gegevens	geen gegevens
Jo-Fan Yu	Independent Outside Director	1.2yrs	geen gegevens	geen gegevens

Gegevens	Laatst bijgewerkt (UTC-tijd)
Bedrijfsanalyse	2026/05/09 08:52
Aandelenkoers aan het einde van de dag	2026/05/08 00:00
Inkomsten	2025/12/31
Jaarlijkse inkomsten	2025/12/31

Pakket	Gegevens	Tijdframe	Voorbeeld Amerikaanse bron ^*
Financiële gegevens bedrijf	10 jaar	Resultatenrekening Kasstroomoverzicht Balans	SEC-formulier 10-K SEC-formulier 10-Q
Consensus schattingen analisten	+3 jaar	Financiële prognoses Koersdoelen analisten	Onderzoeksrapporten van analisten Blue Matrix
Marktprijzen	30 jaar	Aandelenprijzen Dividenden, splitsingen en acties	ICE Marktgegevens SEC-formulier S-1
Eigendom	10 jaar	Top aandeelhouders Handel met voorkennis	SEC-formulier 4 SEC-formulier 13D
Beheer	10 jaar	Leiderschapsteam Raad van bestuur	SEC-formulier 10-K SEC-formulier DEF 14A
Belangrijkste ontwikkelingen	10 jaar	Bedrijfsaankondigingen	SEC-formulier 8-K

Analist	Instelling
Leo Mochizuki	BofA Global Research
null null	Daiwa Securities Co. Ltd.
Masayuki Abe	Daiwa Securities Co. Ltd.

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Recente managementupdates

Appier Group, Inc., Annual General Meeting, Mar 27, 2026

Appier Group, Inc., Annual General Meeting, Mar 27, 2025

Appier Group, Inc., Annual General Meeting, Mar 27, 2024

Insufficient new directors

Appier Group, Inc., Annual General Meeting, Mar 29, 2023

Less than half of directors are independent

Recent updates

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Consensus EPS estimates fall by 13%

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Appier Group, Inc., Annual General Meeting, Mar 27, 2024