500 color matching requests processed in 3 minutes! Yinuohang will use algorithms to "replace" colorists, reshaping the RMB 50 billion automotive coatings market.
In the automotive coating industry chain, color matching capability is evolving from a back-end technical support function to a core competitiveness that determines product delivery efficiency and end-user stickiness. With the accelerated iteration of vehicle models, continuous expansion of original factory color codes, and the explosion of demand for personalized color modification, coating manufacturers are no longer only facing production capacity issues, but systematic contradictions between color development cycles, formulation service response speed, and end-point technical support coverage. To address this industry pain point, Hangzhou Yinuohang Automotive Technology Co., Ltd. has launched the "Intelligent Color Partner Program", providing coating manufacturers with a full-link strategic cooperation solution from digital color modeling to end-point intelligent application.
Color Matching Capability Becomes the Scalability Bottleneck of the Automotive Coating Industry
Traditional color R&D and color mixing rely heavily on technicians' experience and visual judgment. In the CIE LAB uniform color space, even senior technicians need multiple spray tests and corrections when dealing with complex color systems containing effect pigments such as metallic paint and pearlescent paint. Traditional color matching relies on the simplified model of the Kubelka-Munk theory and technicians' empirical correction. When dealing with automotive topcoats containing effect pigments such as aluminum powder and pearlescent powder, the single-angle color difference ΔE*ab is difficult to fully characterize color consistency due to the directional arrangement of pigments and the flop effect.
When the demand for colors grows at a scale of hundreds of types per quarter, formulation matching efficiency, service standardization, and cross-regional capability replication become the key bottlenecks restricting the large-scale expansion of enterprises. At the same time, the structural shortage of industry talents has become increasingly prominent. According to industry survey data, a qualified painting technician often needs more than three years of systematic training and practical experience accumulation, while there is a significant gap in senior color matching engineers with the ability to deploy complex colors, and the gap of high-end technical talents has reached the scale of thousands. The contradiction between the declining willingness of young people to engage in this industry and the long training cycle of technicians further amplifies the restriction of insufficient color service capacity on the development of the industry.
In terms of market space, automotive coatings have become a 10-billion-yuan track. According to public industry data, the size of China's automotive refinish paint market reached about 16.8 billion yuan in 2025, and the overall automotive coating market is close to 50 billion yuan, maintaining an average annual growth rate of more than 8%. The continuous aging of the stock vehicle age structure, the rising frequency of accident vehicle maintenance, and the improvement of consumers' requirements for original-level appearance repair jointly drive the rigid expansion of refinish paint demand. However, mismatched with the growth of market size, color service capacity still relies heavily on manual experience, making it difficult to achieve standardized output and cross-regional replication. This contradiction is particularly prominent in the process of coating manufacturers expanding to national brands.
From Algorithm to End Point, Build Full-Link Digital Color Capability
Color algorithm is the core of Yinuohang's entire technical system. The self-developed color evaluation system of Yinuohang integrates multi-angle spectral reflectance data and high dynamic range image features, uniformly maps the spectral curves collected by the colorimeter and the visual parameters captured by the camera such as texture, flop index and roughness to the same feature space, and completes the multi-dimensional color effect matching of formulations through a deep learning model. The establishment of this evaluation standard enables formulation recommendation to no longer rely on a single color difference index, but to achieve the optimal balance between spectral matching degree, visual consistency and construction tolerance, realizing the leap of color service from empirical judgment to standard quantification. According to the data disclosed by Yinuohang, the system can process 500 color matching requests in parallel within 3 minutes, and the one-time matching success rate of formulations reaches 80%, which significantly reduces the number of laboratory proofing and color matching waiting time.
More critically, this algorithm system supports construction from scratch, rather than only being applicable to preset color libraries. Yinuohang provides coating manufacturers with exclusive algorithm services for their complete paint systems. First, it systematically calibrates the spectral and rheological properties of each color paste of the enterprise, establishes a digital file of color pastes containing the corresponding relationship between pigment concentration and multi-angle reflectance, so that the model can accurately grasp the tinting strength, hue shift and hiding power curve of each color paste. On this basis, the enterprise's historical formulation library and corresponding color measurement data are imported, and the non-linear mapping relationship between formulation composition and measurement response is established through supervised learning, so as to mine the high-dimensional spatial interaction effect of color pastes that is difficult to quantify in manual experience. Finally, based on the above data training, a color reasoning model adapted to the enterprise's own product system is obtained, which supports rapid formulation prediction of new color codes and intelligent optimization of existing formulations. Through this process, the formulation experience and product data accumulated by coating manufacturers for many years are transformed into the enterprise's independent and controllable digital color capability, rather than remaining in the minds of individual technicians.
Algorithm capabilities need to be implemented with tools to release value. Yinuohang has built an integrated software and hardware color solution of cloud algorithm platform, intelligent color measurement hardware and end-point color matching system, bringing the factory R&D end, distributor service end and end-point store application end into the same data collaboration network. The cloud system undertakes formulation database management, algorithm reasoning scheduling and intelligent retrieval, supporting millisecond-level similarity query of millions of formulations; the intelligent colorimeter accurately measures multi-angle spectra and multi-angle texture images, and outputs multi-angle spectral reflectance and particle characteristic data of metallic pearlescent paint surfaces; the end-point color matching system receives the cloud recommended formulations in real time, automatically calculates the gram weight of each component combined with the actual inventory of color pastes, and supports fine-tuning correction and formulation return.
As a result, the standard formulations developed by the factory laboratory can be synchronized to any service outlet through the cloud immediately, and distributors and end-point stores can call the authoritative formulations without waiting for the arrival of technical personnel; the actual measurement data and correction records generated during the end-point color matching process are transmitted back to the cloud in reverse, forming a data closed loop of development, application, feedback and optimization, which provides training samples of real scenarios for manufacturers to continuously improve the color database and algorithm model. According to Yinuohang, this system can help end-point stores improve the color matching efficiency by more than 30%, and at the same time enable coating manufacturers to systematically collect the difference color phenomena caused by climate, light and construction habits in different regions, so as to quickly develop and share regionally adapted formulations. For cross-regional coating enterprises, this not only solves the problem of color matching efficiency, but also the strategic problem of how to realize large-scale end-point coverage of headquarters color technical capabilities.
In addition to color matching, Yinuohang extends its capabilities to the construction link. Its intelligent painting robot integrates embodied intelligence and multi-modal perception technology, and achieves 0.1mm-level dynamic 3D reconstruction through high-precision SLAM real-time positioning and point cloud registration technology, overcoming the automation bottleneck of non-standard part painting. For coating manufacturers, the core value of this equipment is that it can embed the construction process parameter windows of its own products, including viscosity, curing agent ratio, spraying distance, gun moving speed, atomization pressure, inter-layer flash-off time, etc., directly into the robot process library, so that the color formulation and construction process are fully digitized and reach the end point directly through intelligent equipment.
From Selling Products to Selling Services, Team and Progress Support Industry Paradigm Shift
The business model of Yinuohang's "Intelligent Color Partner Program" is essentially to help coating manufacturers transform from a single product supplier to a color solution service provider. What coating manufacturers output is no longer a single paint product, but a full-link color solution covering color R&D, formulation service, end-point color matching and construction application. The target users focus on automotive coating manufacturers with national expansion needs and facing the bottleneck of color service capacity, and realize commercial value through the combination of algorithm authorization, hardware sales and continuous data services.
The team background is an important support for Yinuohang to promote this model. Zhuang Weizhen, Founder and CEO, has more than 20 years of experience in the automotive aftermarket. He founded auto parts trading companies in the early years and served as the regional general manager of the secondary service system of FAW Car, with in-depth understanding of the automotive maintenance industry chain. Yang Yixian, Chairman and Co-Founder, used to be a senior executive of Siemens Greater China and President of China Wanma Group, with 30 years of senior technical and management experience. Han Jilin, Director and Co-Founder, used to be the Senior Vice President of Yum China and General Manager of KFC Brand, with rich experience in chain operation and large-scale management. He Huan, CTO, is a PhD from Zhejiang University, used to be a 19A-level expert of Huawei, with 12 years of front-line R&D experience in software, hardware, algorithm and chips. According to public information, Yinuohang's core R&D team has nearly 55 members, including 6 doctors and postdoctors, and more than 30 masters, whose members graduated from well-known domestic and foreign universities such as Peking University, Zhejiang University, Harbin Institute of Technology, Shanghai Jiao Tong University, covering professional fields such as artificial intelligence algorithm, machine learning, mechanical automation and data science. As of August 2026, Yinuohang has obtained 22 invention patents and more than 40 software copyrights.
In terms of business progress, Yinuohang was founded in 2016. It completed tens of millions of yuan of Series A financing in June 2022, exclusively invested by CGC Capital, and completed Series A+ financing in September of the same year. After years of accumulation, Yinuohang's platform has accumulated more than 1 million original factory color formulation databases of real vehicles, its business covers 30 provinces, municipalities and autonomous regions across China and overseas markets, providing digital color solutions for more than 700 end-point stores and upstream coating factories, and the rework rate of its cooperative repair shops is only 0.6%, far lower than the industry average. In terms of industrial cooperation, Yinuohang has established in-depth technical cooperation with international coating enterprises such as Svit (formerly BASF), and officially became the general agent of Glasurit 88 Flash Paint in Chinese Mainland in July 2026.
The competition paradigm of the coating industry is undergoing profound changes. In the past, product quality, price system and channel coverage were the core elements of competition; in the future, the technical service capability and end-point digital connection capability built around products will become more decisive competitive barriers. From a single color to a set of algorithms, from a set of formulations to a cloud service system, color is evolving from a traditional technical link in the coating industry chain to a new digital capability that connects upstream and downstream, precipitates data assets and builds service barriers. For coating enterprises, what they compete for in the future may no longer be just what kind of coatings they produce, but whether they can quickly solve color problems, whether they can serve every end point well, and whether they can truly deliver products and technical capabilities to customers.