AI new metal materials company secures tens of millions in financing by compressing 10-year R&D cycle to 2 months | Exclusive report by Yingke

Author | Wu Huaxiu

Editor | Yuan Silai

Yingke learned that Deep Material, an AI + new metal material R & D company, recently completed a Series A financing of tens of millions of yuan. The investment was participated in by Heshi Family Capital and Chenhui Capital successively. The funds from this round of financing will be used for the R & D iteration of new materials, the upgrade of the high - throughput automated laboratory, the development of artificial intelligence models, and the large - scale application in vertical industry scenarios.

It is worth noting that the company's self - developed software - hardware integrated material intelligent agent (DM Agent) will be officially released on September 10th, further promoting the implementation process of its technology.

"Material R & D cannot be achieved overnight just by creating a model. The difficulty lies in the data closed - loop and industrial implementation," said Wang Xuanze, the founder. In his opinion, this is why there have been many listed companies in the fields such as medicine where AI is applied, but few have succeeded in the metal material field. What the investors value is that Deep Material has established an industrialization path in the "AI + materials" field and has the conditions for rapid expansion.

Founded in 2021, Deep Material creatively embedded artificial intelligence into the entire process of new metal material R & D, self - building everything from algorithm models, high - throughput laboratories to material data systems. This path is closely related to Wang Xuanze's background: he graduated from Shanghai Jiao Tong University with a bachelor's and master's degree, majoring in artificial intelligence. He grew up in Anshan, Liaoning, a major steel - producing city, in a family with a materials background. In 2015, he first realized that AI might change material R & D, but at that time, the technology, computing power, and data conditions were not yet mature. Five years later, he saw the opportunity approaching. "In the field of metal materials, customers are most concerned about performance indicators, which is exactly the direction that AI can precisely optimize."

In the process of metal material R & D, data is a recognized bottleneck: difficult to obtain, with incorrect dimensions, and poor consistency. Deep Material chose to bypass these obstacles: using self - developed high - throughput equipment to generate high - consistency experimental data at low cost and high efficiency, and then having large models dispatch professional small models to complete formula and process optimization, forming a multi - modal integrated "material intelligent agent" + high - throughput experimental system. Under this system, the R & D cycle is compressed from the traditional several years or even more than a decade to within two months at the fastest, and the cost is reduced by one to two orders of magnitude.

(Image source/Enterprise)

This ability also led Deep Material to make different choices in its business model. Wang Xuanze believes that future material companies must build "dual capabilities": improving R & D efficiency through algorithms and having the ability to implement industrialization. "The business model of simply providing R & D services has limitations," he emphasized. "If the large - scale production link cannot be controlled, the value of R & D will be weakened." Therefore, since 2023, the company has shifted from undertaking order - based R & D to independently initiating R & D projects for material categories with large market demand and high process barriers.

The first batch of products is high - strength aluminum alloy for 3D printing, with a strength of over 550 MPa, meeting aerospace - grade requirements. Since it does not contain precious metal components, the cost is only one - third of that of overseas similar products, having a significant cost advantage. These materials have entered the verification and procurement processes of aerospace research institutes and leading 3C OEM manufacturers.

This strategic upgrade stems from Deep Material's forward - looking judgment on the pattern of the metal additive manufacturing industry. The penetration rate of global 3D printing metal materials is still in the early stage. According to data from Precedence Research, the global metal additive manufacturing market size was approximately $5.87 billion in 2024 and is expected to grow to $6.68 billion in 2025. It is expected to exceed the $20 billion mark in the next decade, with a compound annual growth rate of approximately 13.7%. However, in terms of specific material categories, there are less than thirty grades of metal materials suitable for stable printing, and they are highly concentrated in the conventional grades and properties of materials such as aluminum alloys, superalloys, titanium alloys, and stainless steels, making it difficult to meet the customized requirements for special properties such as high strength and lightweight in fields such as aerospace and consumer electronics.

"The biggest opportunity in this industry lies in using materials to break through the limitations of downstream applications, such as reducing the excess weight of structural parts in aerospace and consumer electronics," said Wang Xuanze. In the past decade, the attitude of domestic manufacturing industries towards new materials has been changing from cautious to proactive, especially consumer electronics manufacturers. "They will actively ask if we can develop new materials that are light, strong, and inexpensive."

Deep Material's business is not limited to materials themselves. The high - throughput laboratory equipment and material intelligent agent solutions are also entering the R & D systems of top domestic universities, national - level laboratories, and manufacturing enterprises. This model of "self - producing data - self - developing models - implementing on production lines" has opened up more application scenarios for it.

In the next two years, they hope to achieve mass - production profitability for one or two materials; in five to ten years, cover more industries and complete listing. For the longer - term goal, Wang Xuanze summarized it in one sentence: "Let human progress no longer be restricted by materials."

Investors' Views:

Heshi Family Capital: Heshi Family Capital, the investor in this round, is a "patient capital" focusing on the next - generation digital and intelligent additive manufacturing field. Although Heshi Family Capital is generally cautious about the metal material industry dominated by traditional giants, the core logic of this investment is that it highly recognizes Deep Material's "digital breakthrough" ability to combine AI with digital and intelligent additive manufacturing. Heshi Family Capital hopes that Deep Material's DM Agent platform can accelerate low - cost material research and innovation in new material product applications and become the "DeepSeek" in the new metal material field.

Chenhui Capital: At the critical stage of the global manufacturing industry's intelligent transformation, Chenhui Capital invested in Deep Material because it firmly believes in the "AI + new materials" track and the company's disruptive model. By integrating high - throughput experimental platforms, materials informatics, and deep neural networks, Deep Material has upgraded traditional material R & D from a "trial - and - error" approach to a "predictive" approach, effectively solving the pain points of long R & D cycles and high costs. Its full - chain layout not only demonstrates technological leadership but also shows strong industrialization potential. We look forward to jointly promoting China's leap from following to leading in the field of high - end metal materials.