AI pricing and optimization
We study reinforcement learning for pricing within agreed operating rules. Our joint work on how models adapt from offline data to online settings was accepted at an ICML 2026 workshop.
HayanMind develops Monetai, an AI price optimization solution specialized in time-sensitive inventory. It uses demand, sales and inventory data to guide price decisions. Our research and operating experience also support pricing projects across apps and digital services.
Demand changes. Inventory changes. Price decisions need to account for both. We connect pricing research to business operations.
HayanMind is an AI dynamic pricing company. Our product Monetai specializes in time-sensitive inventory, while our pricing research and app experience support projects across digital services.
Monetai specializes in AI price optimization for time-sensitive inventory. Each project starts with a review of data and integration needs.
Experience in app monetization, purchase behavior and price sensitivity remains part of our technology. We assess how these models fit each digital service's data and pricing goals.
Demand forecasting, price elasticity and willingness-to-pay research inform our models. Prices are selected within agreed operating rules, and observed results inform subsequent decisions.
We analyze demand, booking or purchase behavior, available inventory and seasonality to understand how customers respond to prices.
We define business goals, permitted price ranges, margin thresholds and approval rules with each customer before prices go live.
Our learning engine draws on joint research with KAIST to select price candidates within operating rules and use sales results to inform the next decision.
Experience across apps and enterprise projects informs our pricing work. App Pricing Lab contributes app-market observations, while models and data sources are chosen for each use case.
Redesigned the pricing structure with an AI dynamic pricing model, factoring in demand patterns and seasonality.
Re-derived price points using willingness-to-pay prediction and elasticity modeling.
Previous app projects used purchase prediction and personalized promotions. This experience continues to inform our work in digital-service pricing.
We evaluate pricing changes against each project's agreed business metrics and operating conditions.
*Selected current and past engagements. Client details remain confidential.
We review your pricing structure, available data and decision process to agree on the scope and metrics to evaluate.
We develop suitable demand and price-response models, agree on operating rules, and plan integration with your existing systems.
We introduce the engine within the agreed scope, monitor its results against the existing policy, and use the evidence to refine pricing decisions.
Monetai is our pricing operations product. App Pricing Lab and RedKiwi contribute market observations and experience running digital services.
Monetai specializes in AI price optimization for time-sensitive inventory. It connects to existing business systems, calculates prices within agreed policies and learns from sales results. Integration is designed for each customer.
Learn More →App Pricing Lab tracks in-app prices, rankings and price changes on the App Store and Google Play. These observations support our research in app and digital-service pricing.
Learn More →The English-learning app we operate. RedKiwi is where we encountered monetization challenges firsthand and developed pricing AI to address them.
Experience operating our own digital service
Learn More →HayanMind started in a KAIST graduate research lab in 2017 and went on to focus on pricing research. Today we work with KAIST and Korea University's DAIS Lab to turn academic models into production pricing systems.
We study reinforcement learning for pricing within agreed operating rules. Our joint work on how models adapt from offline data to online settings was accepted at an ICML 2026 workshop.
Together with DAIS Lab, we develop models that predict user behavior and willingness-to-pay from in-service signals.
A record of industry-academic research through the Ministry of SMEs and Startups' Collabo R&D program.
Selected for Google's Asia-Pacific AI startup program.
Partners & programs
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HayanMind Inc. 주식회사 하얀마인드
1208, 12F, BLOCK77, 17, Seocho-daero 77-gil, Seocho-gu, Seoul, South Korea [06614]
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