AI+ visual analysis to create Haiyun's high-quality product “Smart Alert Brain”

Artificial intelligence, big data, and advanced algorithms are three essential pillars driving the digital transformation today. Many big data companies have evolved into AI-focused enterprises, integrating data visualization and analysis into their core operations. Haiyun Data, initially known for its data visualization solutions, began exploring AI last year. In March of this year, it officially launched a lip-reading identification technology, and in August, it unveiled its comprehensive AI strategy. This rapid transformation—whether driven by market trends or business evolution—will ultimately depend on how effectively big data and AI technologies can be applied in real-world scenarios. Haiyun has been deeply involved in public security, aiming to make the industry "intelligent" through smart systems. The company's "Smart Alert Brain" is a high-quality product that combines AI with visual analytics. Launched on December 8th, this product is built on the MapEase 6.0 platform and integrates AI and data visualization to enhance public security operations. By combining platform capabilities with real-world public security needs, it has developed over 200 industry-specific functions across 40 domains. So far, Haiyun’s Smart Alert Brain has been successfully deployed in more than one-third of provincial and municipal public security bureaus, significantly improving efficiency. After implementation, the time required for intelligence analysis was reduced by 70%, while operational efficiency increased by 50%. At a recent conference, Haiyun’s founder and CEO, Feng Yicun, demonstrated the upgraded "Smart Alert Brain." During the demo, he used facial recognition to access the system and issued voice commands to a robot, showcasing accurate recognition and seamless interaction. A police officer on-site participated in the process, from receiving orders to executing them, highlighting the system’s practicality. The Smart Alert Brain also features predictive capabilities. For instance, if individuals with a history of drug use tend to gather at night, the system can predict potential drug-related activities. It can also analyze case clues, such as suspects’ social networks and travel patterns, helping law enforcement identify criminal groups and solve multiple cases. Additionally, the system allows users to control maps via voice commands, display video footage of incidents, and view nearby emergency resources like hospitals and police stations. This gives senior commanders real-time decision-making and dispatching capabilities, ensuring faster response times during emergencies. According to Feng Yicun, the Smart Alert Brain enables users to see real-time information about nearby police units, crime locations, suspect routes, and key suspect records—all presented visually for quick judgment. The goal is to make all command and intelligence centers intelligent and responsive, ensuring that orders reach frontline personnel instantly and that critical information is delivered in real time. Currently, Haiyun’s Tuyi platform has expanded into sectors such as public safety, transportation, smart cities, and civil-military integration. While AI technology holds great promise, the path to productization remains challenging. Many AI startups have made significant technological advances but struggle to translate them into real-world applications. However, in the deep-rooted domain of public security, Haiyun has successfully integrated AI into practical scenarios, building robust products and gaining industry credibility. Why is AI still difficult to commercialize? One reason is the gap between innovation and application. While many AI companies focus on cutting-edge research, the second half of the year often emphasizes product development and commercial deployment. Companies like Star AI have turned image recognition into widespread applications, especially in the security sector, where demand for facial recognition is high. Speech recognition firms are also exploring opportunities in the IoT space. There is a fundamental difference between AI+industry and industry+AI. The former, similar to Ctrip, represents the Internet transforming traditional industries. The latter, like autonomous driving, involves AI being embedded within an industry itself. Today, many companies are competing in the AI space—giant tech firms, industry upstarts, and new startups. Some face criticism for lacking commercial success. Whether it's easy or not, the next step in AI productization will determine who survives and thrives in this rapidly evolving field.

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