BackFrom July 31 to August 3, the 23rd China Digital Entertainment Expo and Conference (2026 ChinaJoy) was held at the Shanghai New International Expo Center. Under this year’s theme, “与AI同游” (“Journeying with AI”), the event gathered nearly 900 participating companies to showcase the latest innovations in gaming, digital entertainment, artificial intelligence, and cutting-edge technology.
Making a prominent appearance at the BTOB business pavilion with a dual-booth setup, RixEngine and RixDesk showcased an End-to-End Growth Ecosystem featuring three core products: RixDesk (One-Stop AI Marketing Agent), Rix AI SDK (AI Monetization Agent for Developers), and RixSaaS (AI-Powered Programmatic Ad Platform Deployment & Operations). During the event, the team publicly shared its framework and core capabilities for building an AI Decisioning Engine for Digital Advertising for the first time, highlighting a major R&D focus over the past two years.
I. The Third Paradigm Shift in Advertising: From Bidding Efficiency to Decision Intelligence
According to RixEngine, computational advertising is undergoing a third paradigm shift: transitioning from contract advertising to real-time bidding, and now entering the era of Decision-driven Advertising centered on business goals. The core capabilities of advertising systems are evolving beyond ad delivery and real-time bidding toward the end-to-end orchestration of data, strategy, decisioning, and execution.
Over recent years, the complexity of the advertising industry has surged. Faced with longer marketing funnels, increasingly diverse traffic scenarios, and stricter cost-efficiency requirements, RixEngine chose to extend its business capabilities directly into the decision-making layer. Following nearly two years of sustained investment, the team has successfully built systematic capabilities around its "AI Decisioning Engine for Digital Advertising," officially debuting them at this year’s ChinaJoy.
II. The Core Logic of AI Decisioning: Four Key Capabilities Power a Closed-Loop Decisioning System
Traditional bidding advertising heavily relies on rule-driven models and predictions—often a process where "humans set the conditions, and the system predicts and bids for impressions." In contrast, AI decisioning is "goal-driven" and capable of "automated execution by AI agents," with optimization centered on business outcomes such as ROI and CVR.
Integrated with advanced AI Agent capabilities, this system allows advertisers to define business objectives through natural-language interactions. The AI then automatically decomposes the targets, formulates strategies, executes campaigns, and leverages self-evolving reasoning and learning. Its core logic is driven by four key actions:
End-to-End AI Decisioning: By integrating user behavior, contextual signals, historical performance, and real-time feedback, the system utilizes Deep Neural Networks (DNN) and attention mechanisms to accurately predict click-through rate (CTR) and conversion rate (CVR). Combined with real-time Reinforcement Learning (RL), it continuously iterates the optimal strategy within a post-back closed loop.
Dynamic Routing & Inventory Tiering: Leveraging inventory quality assessment, user intent recognition, and AI-powered risk control, the system classifies inventory into S/A/B/C tiers based on quality, value, and risk. It identifies low-quality and fraudulent traffic in milliseconds, ensuring high-value inventory can be prioritized for higher-performing demand and use cases.
Intelligent Bidding & Optimal Budget Matching: Based on AI value prediction, dynamic pacing, and bid shading technologies, the system identifies the optimal balance between bidding cost and expected performance.
Performance Feedback & Optimization: Continuous learning is central to AI decisioning. The system relies on actual post-campaign results (post-backs) to continuously train its models. Through real-time RL, it identifies effective actions and corrects strategic deviations, allowing the AI to make smarter decisions in subsequent bids and achieve increasingly precise delivery.
Currently, RixEngine has deployed these capabilities to its in-house DSP advertisers and serves dozens of DSP partners across Europe and the Americas. The system excels in critical areas such as high-value user identification, inventory screening, compliant ID mapping, lookalike audience expansion, and data privacy protection. By fusing Multi-Source Data Intelligence with RixDesk’s AI Agent capabilities, RixEngine further closes the business loop—from data processing and AI-powered strategy decisioning to automated execution and performance feedback. This ensures the AI doesn’t just "calculate better" but continuously adjusts its strategies in line with business objectives.
III. Three Core Products: Bringing AI Decisioning into Real Business Scenarios
Centered around its AI Decisioning Engine for Digital Advertising, RixEngine has developed a suite of three core products that cover ad delivery, developer monetization, and programmatic platform operations. These solutions translate unified advertising data, algorithms, and decision logic into actionable tools for various industry players.
RixDesk: One-Stop AI Marketing Agent — Integrating AI Across the Marketing Funnel Tailored for advertisers and marketing teams, RixDesk is powered by AI Agents and covers strategy planning, audience insights, budget management, creative development, campaign optimization, and performance analysis. It empowers teams to seamlessly bridge market insights with campaign execution, improving user acquisition decision-making and campaign efficiency. (RixDesk debuted with a dedicated independent showcase area at ChinaJoy).
Rix AI SDK: AI Monetization Agent for Developers — Unleashing Inventory Value Built for game and app developers worldwide, Rix AI SDK connects to high-quality global ad demand through a lightweight SDK. By analyzing inventory characteristics, user value, regional markets, and historical performance, it optimizes demand matching, dynamic bidding, and overall monetization strategies—helping developers improve fill rates and build more sustainable ad revenue.
RixSaaS: AI-Powered Programmatic Ad Platform Deployment & Operations — Your New Operations Partner Designed for DSPs, AdXs, and programmatic ad platform operators, RixSaaS reduces the technical and operational complexity of programmatic platform deployment. Powered by AI Digital Employees, it provides robust support for data analysis, strategy optimization, risk control, business growth, and customer service, helping teams elevate their day-to-day operational efficiency.
From advertising campaign delivery and inventory monetization to platform deployment, RixEngine is seamlessly integrating AI decisioning into every facet of the business workflow, building an intelligent ecosystem that understands objectives, formulates strategies, and executes them autonomously.
Though ChinaJoy 2026 has drawn to a close, the transformative impact of AI on advertising and digital commerce is just beginning. Moving forward, RixEngine is committed to driving the widespread adoption of its AI Decisioning Engine across more global ad scenarios—ensuring every impression delivers tangible business value and working with clients and partners worldwide to unlock new opportunities for AI- and data-driven growth.
