Key points of investment:
An AI solution provider incubated in the Chinese Academy of Sciences and focused on application implementation. Yuncong Technology was founded in 2015. Although it started late, it has built the country's top 3 platforms at the same time with deep technology accumulation. Founder Zhou Xi was previously the deputy director of the Institute of Electronics and Information Technology of the Chinese Academy of Sciences. Since 2006, he has led the team to win numerous championships in the Artificial Intelligence World Series. The core products are human-robot collaborative operating systems and artificial intelligence solutions, which are deeply involved in various industry scenarios such as governance, finance, mobility, commerce, and pan-AI.
The large model's forward-looking layout and self-developed technical architecture set 4 world records. The company is centered on computer vision technology, and its main technology is leading in authoritative data sets. The Calm Big Model was released on May 18, 2023. According to the SuperClue April 2024 list, the Calm Big Model V1.5 ranked 7th among domestic big models. Using the company's self-developed “All in One” infrastructure, the paper was selected as ACM MM, a top conference in the field of computer science multimedia. The evaluation results reached SOTA on 4 public data sets. The technology path is similar to the current OpenAI latest ideas.
It has accumulated advantages in the industry, fully upgraded product lines, and ecological cooperation with Huawei Shengteng. 1) Focus on industry implementation. The company will raise funds for the development of large models of industry elves. Accumulation of past industry experience helps to quickly complete the migration from general models to professional models. 2) Explore AI Agent capabilities. The company's CWOS platform focuses on planning and application capabilities, improving AI algorithm model production efficiency, improving decision-making efficiency, and exploring industry intelligence upgrades and breakthroughs in new business scenarios. 3) The product line has been fully upgraded, and it has been implemented in cooperation with B-side customers in multiple industries. 4) Huawei's Shengteng ecosystem cooperated to launch a calm training and promotion all-in-one machine to meet the privatization deployment needs of enterprises.
Based on smart governance, financial, travel and business scenarios are developing rapidly. As of 2023, it has covered more than 100 financial institutions (including 6 major state-owned banks), hundreds of civil hubs (including 9 important airports in the top 10 domestic airports), and various scenarios such as politics, schools, and scenic spots in 30 provincial administrative regions across the country. Increased generality accelerates the layout of innovative application scenarios. The company has made progress in manufacturing, energy, education, cultural tourism and other scenarios, and is working with major customers to create benchmark industry models and implementation applications. The various sections expect: 1) smart governance will be pressured by the macroeconomic situation in the short term; 2) the finance, travel, and business sectors will bring new volume along with the implementation of large models and the recovery of travel and offline commerce; 3) the completion of fund-raising projects will drive the development of innovative fields.
Considering 1) smart governance is affected by the macro environment, growth is expected to resume in 2025; 2) it will take time to commercialize the big model of the industry, and revenue in the fields of finance, travel, commerce, and innovation is expected to begin to be reflected in 2025. We expect the company's revenue to grow as high as 52% in 2025, and chose 2025 as the valuation year. Revenue forecasts for 2024-2026 are $803, 12.21, and $1,609 million, and net profit forecasts to mother are -4.59, -3.52, and -275 million yuan.
The target market value was 14.81 billion yuan (12x2025 PS), which gave it a “buy” rating for the first time.
Core hypothetical risks: AI technology falls short of expectations; rapid technology iteration and increased industry competition; demand for technicians may increase; macroeconomic recovery falls short of expectations.