Recently, the industrial robot company Guangdong Topstar Technology Co., Ltd. (hereinafter referred to as “Topstar”, 300607.SZ) disclosed its 2025 annual report.
Data show that the company achieved annual operating income of 2.510 billion yuan, a year-on-year decrease of 12.59%; however, the net profit attributable to shareholders of the listed company was 73.8725 million yuan, a year-on-year increase of 130.12%, successfully turning losses into profits.
This report card of “reducing revenue and increasing profits” reflects that this nearly 20-year-old industrial automation company is undergoing a profound structural adjustment.
Under the strategy of actively shrinking low-margin project-based businesses and concentrating resources on industrial robots and embodied intelligence, Topstar is trying to answer a question: When “subtraction” results in short-term profits, where will the next growth come from?
Looking through the financial report, the most obvious change of Topstar in 2025 is the reconstruction of the business structure.
The company took the initiative to compress its smart energy and environmental management system business, and revenue from this segment fell 25.55% year-on-year to 915 million yuan.
This segment used to be an important component of Topstar’s revenue, but its gross profit margin was negative and it occupied a large amount of capital.
The company said in its performance report that the divestiture of the business was “basically completed” and subsequent revenue will decline further.
The price of contraction is the decline in revenue, which will drop from 2.872 billion yuan in 2024 to 2.510 billion yuan.
The annual revenue proportion of the product business increased by 6.67 percentage points, and the gross profit contribution accounted for 60%, becoming the main pillar of the company’s profits.
The gross profit margins of core product lines such as industrial robots and injection molding equipment have increased, and the overall gross profit margin has increased from 14.59% to 28.25%.
Zhang Xiaorong, president of the Deepin Technology Research Institute, believes that this strategy of “abandoning low gross profits in exchange for profits” has significant financial improvement effects in the short term.
“Although the revenue is less, cutting off unprofitable businesses and directly turning losses into profits will make the company’s finances healthier. In the long run, focusing money and energy on the main business will make it more competitive. This approach of giving up scale first and preserving profits is very pragmatic. Short-term pain will be exchanged for long-term growth.
Development is a wise choice for manufacturing companies.
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Zhou Di, a senior engineer at Fangrong Technology and an expert in the Ministry of Science and Technology’s National Science and Technology Database, added that in the long run, focusing resources on core industries such as industrial robots will help build technical and market barriers.
“Although the short-term scale is under pressure, development is more focused and sustainable.”
However, an unavoidable question is: after the smart energy business is basically divested, can other businesses support future growth?
Topstar stated that future growth will be based on the “three-step strategy in the new decade”: the first step is to “build a stronger base” and consolidate Cartesian coordinate robots and injection molding supporting equipment; the second step is to “build strong equipment” and deepen the layout of CNC machine tools, injection molding machines, etc.; the third step is to “consolidate embodied intelligence” and build a global intelligent ecosystem.
The performance report shows that the company’s robot body sales will reach 10,437 units in 2025, a year-on-year increase of approximately 13.7%. However, the overall revenue of the industrial robot and automation application system segment fell 9.24% year-on-year to 685 million yuan.
This means that sales volume growth has not fully offset the revenue pressure caused by price or structural changes.
How to convert sales advantage into sustained growth in revenue and profits is still a challenge facing the company.
As for the reasons for the decrease in revenue, Topstar explained that the company’s automation application system business focused on 3C head customers in the early stage, while orders and revenue from customers in other industries decreased; the company focused more on the research and development and layout of “robot+” applications, improved standardized production capabilities, and reduced the business proportion of personalized projects.
However, as the depth and breadth of cooperation with 3C head customers increases, the scale of related business orders continues to grow, with orders on hand at the end of 2025 increasing by 116.64% year-on-year.
In terms of industrial robots, the company’s product competitiveness continues to improve, its large customer strategy has achieved results, its process and application advantages have further emerged, and its operating income has increased year-on-year. Among them, self-produced multi-joint robots have increased by 25.32% year-on-year, and Cartesian coordinate robots have increased by 7.35% year-on-year. The annual shipment volume of robot products is approximately 12,000 units.
At a time when embodied intelligence has become the hottest track in the market, Topstar did not choose the grand narrative of “universal humanoid robots”, but instead started from the injection molding scene that it is most familiar with.
In 2025, the company launched the humanoid robot “Xiaotuo” used in injection molding workshops, as well as the four-legged robot “Xingzai”, AI flexible sorting workstation and other products.
This strategy is regarded by the outside world as “making a hammer by looking at the nail.”
Topstar also pointed out in an interview that the company will analyze and deconstruct the injection molding scenario process to form a universal process package suitable for various industrial scenarios, and use the universal characteristics of the injection molding scenario to expand horizontally to more industries.
At present, the main application scenarios of “Xiaotuo” include material picking, palletizing, and packaging in warehousing and logistics, as well as autonomous loading, unloading, and sorting in production.
How is this “scenario first” approach different?
In Chang Hsiao-rong’s view, embodied intelligence is still a “castle in the air” and lacks real implementation scenarios.
“Topstar starts from the injection molding workshop and is more down-to-earth. It is faster to implement. It can be tested directly with existing customers and can be used in factories soon. Commercialization is more stable. Factories have real needs and are willing to pay, so they can make money quickly.”
Zhou Di also pointed out
, relying on rapid verification by existing customers, the cost is more controllable and the return on costs is faster. “The certainty of profit is much higher than that of the general route.” However, from injection molding to a wider range of industrial scenarios, and even business, services, and homes, the technical obstacles of cross-scenario reuse cannot be ignored.
Topstar admitted that the main challenges lie in high data costs, weak adaptability, and insufficient generalization capabilities.
To this end, the company and Zhipu Huazhang jointly established Matrix Zhituo to develop a low-cost, highly adaptable portable gripper data collection solution to lay a data foundation for embodied intelligent model training.
This is also a key part of the company’s construction of a “scenario + product + data + AI” business closed loop.
In the competition with the quadruped robot “Xingzai”, in the face of established companies such as Yushu Technology and Yunshenchen, Topstar’s strategy is to use it as an extension of the robot product matrix to form a synergistic effect with the “Tuoxingji” series of embodied intelligent products, industrial robots, and AI workstations to provide differentiated overall solutions rather than simply competing for single products.
The robot industry in Guangdong Province, where Topstar is located, is booming.
Data show that in 2025, Guangdong Province’s industrial robot output was 336,300 units, accounting for 43.5% of the country, ranking first in the country for six consecutive years; service robot output was 15.1821 million units, accounting for 81.7% of the country.
As the largest province in the country’s robotics industry, Guangdong Province has formed a full industrial chain layout covering software, hardware, and ontology.
Zheng Lei, chief economist of Samoyed Cloud Technology Group, analyzed that this industrial cluster provides triple support for Topstar: first, the supply chain response is extremely fast, and the Greater Bay Area has a complete robot supply chain, with “iteration speed 10 times that of Silicon Valley and cost only 1/10”; second, the
The richness of scenarios leads the way. Guangdong has all 31 manufacturing categories. Topstar’s 15,000 existing customers are concentrated in the Pearl River Delta, and the cost of test verification and data collection is extremely low. Third, the collaboration between industry, academia and research is efficient. Shenzhen’s “Robot Valley” gathers institutions such as Southern University of Science and Technology and the Chinese Academy of Sciences to form “basic research”
– Achievements transformation” closed loop.
However, the large-scale implementation of embodied intelligence in the industrial field still faces key bottlenecks. The biggest obstacle currently is the “data dilemma.”
Zheng Lei believes that the supply of high-quality data is insufficient, including high collection costs, difficulty in extracting tacit knowledge, lack of abnormal data, and barriers to “data governance” in factories.
Zhang Xiaorong said that hardware and algorithms are still the bottleneck. “Hardware is expensive, the hands are not dexterous enough, and the algorithm is not smart enough. It is difficult to use in different scenarios, and the factory environment is complex and costly to modify.” Zhou Di added that insufficient technological maturity, high overall machine costs, and imperfect ecology for industrial scene adaptation are also constraints.
Regarding the application prospects in the next 3 to 5 years, Zheng Lei believes that industrial embodied intelligence will be the first to be implemented in structured industrial scenarios, such as handling, sorting, loading and unloading, and logistics warehousing on a large scale. These environments are controllable, tasks are standardized, and ROI is clear; 2025 is regarded as the “first year” of implementation, and “semi-autonomous + local group collaboration” will become an important breakthrough.
Zhang Xiaorong gave a more specific scenario prediction: injection molding, 3C electronic loading and unloading, automobile assembly, logistics handling, etc. “These places have simple processes, high repetition, large demand for labor replacement, and easy promotion.”
Topstar’s 2025 annual report outlines a typical transformation sample of a traditional industrial automation company at the intersection of industrial cycles and capital booms.
By proactively shrinking inefficient businesses, the company has achieved a financial turnaround; by betting on embodied intelligence, the company is trying to occupy a place in the next wave of technology.
But the challenges are equally clear. The endogenous growth of the product business has not yet fully developed. The migration of embodied intelligence from the injection molding scene to the broader market still needs to cross data and technology thresholds. Competitors, both startups and peers, are accelerating their deployment.
Topstar has chosen an “unsexy” but solid path: come from industry and go to industry.
Whether this road can be successful will depend on the speed of its “scenario + product + data + AI” closed loop implementation, as well as its ability to convert existing customers accumulated over the past 20 years into the first batch of paying users of embodied intelligence.
This long-distance race has just begun. Whether the profits gained through “subtraction” will eventually be transformed into “additional” growth, time will tell the answer.
