Damao Technology, known in Chinese as 达卯科技, has reportedly completed a new financing round of approximately RMB 200 million for software that links AI computing demand with electricity and energy operations. The round arrives as China’s AI buildout forces data-center operators, power providers, and industrial users to think more carefully about when and where computing workloads run.
National Business Daily reported the financing on September 23, and Beijing News independently reported the same approximate amount. Neither report names the investors in the new round. Securities Times likewise said the current-round investors had not been disclosed. That means the news should not be framed as a round led by CATL, SenseTime, Cambricon, or any other existing shareholder.
The company name is the only English-style rendering supplied in the source material, so Damao Technology should be treated as a transliteration rather than a confirmed legal English name. The reports describe the firm as an AI energy-operations business focused on coordinating computing power and electricity, virtual power plants, and related energy scenarios. It is a narrower proposition than building a model or a chip: Damao is trying to help high-demand digital workloads operate alongside a physical energy system.
The theme is already familiar to readers of EastFrontier’s coverage of AI inside energy operations. The difference here is company-level execution. National policy may encourage AI in energy systems, but individual operators still need software that can connect a changing compute load to power availability, price signals, maintenance decisions, and grid constraints.
The funding and its undisclosed investors
The approximately RMB 200 million figure is a reported total, not an exact disclosed amount. The sources do not identify a series label, valuation, ownership percentage, financial instrument, terms, or closing date. They also do not say how the money will be allocated in a formal financing document.
That lack of detail is not unusual for an early-stage private round in China, but it changes the language that can be used responsibly. The company has reportedly completed new financing. It has not publicly disclosed a named lead investor for this round. It would be inaccurate to connect the current capital directly to the company’s older backers.
The reports do provide context on an earlier transaction. National Business Daily and Beijing News say Damao completed an approximately RMB 100 million A+ round in October 2025, led by Puquan Capital, a fund affiliated with Contemporary Amperex Technology Co., Limited, or CATL. The outlets also say the company’s shareholder lineup includes CATL, SenseTime, and Cambricon. Those facts describe prior relationships, not participation in the September 2026 round.
That distinction is more than legal housekeeping. The difference between an existing shareholder and a new-round investor can signal whether a company has attracted new capital, secured follow-on support, or raised under a different commercial thesis. The available reports do not allow that conclusion here.
Beijing News says Damao was founded in 2021 and is headquartered in Shanghai’s Xuhui district. It presents the company as an energy-AI specialist, a useful description because its problem sits at the intersection of two fast-moving systems: the growth of AI computing and the need to operate electricity assets efficiently.
A software layer between compute demand and power operations
The reports say Damao uses a self-developed vertical energy large model and an AI-agent cluster. They name products for computing-power/electricity coordination, AI virtual power plants, and intelligent operations and maintenance. The source material gives a particularly long Chinese label for one core system: 算电协同2.0平台·AIDC绿电直连能源运营操作系统. No official English product name was provided, so a descriptive English translation would be a gloss, not a company-certified brand.
The idea behind such a system is relatively straightforward. AI workloads can create large and uneven power demand. A data center may need to decide when it can shift non-urgent processing, how to match a load to available renewable generation, or how to respond when grid conditions change. An energy operator may need to balance those workloads with maintenance needs and other customers.
Virtual power plant software is often used to coordinate distributed energy resources or flexible demand. In Damao’s case, the sources place that software alongside AI computing coordination. This does not establish that the company is a licensed electricity-market operator or that it operates a national virtual power plant. It describes the type of digital system the company says it is building for energy scenarios.
There is a broader economic reason investors may care. As China adds more AI servers, energy availability and the timing of demand become more strategic. EastFrontier’s earlier look at AI data centers and the green-energy challenge examined the tension at a sector level. A company like Damao is trying to address part of that tension through operating software rather than by building a power plant or a new chip.
How to read the reported performance figures
Securities Times identified the company’s CEO in Chinese as 简煜忞 and reported his view that the new funding would support research and development, model and platform upgrades, and industrial integration. Those are future uses described by an executive, not a released investment plan.
The outlet also reported a Damao deployment at SenseTime’s Lingang intelligent-computing center. Securities Times reported a Damao deployment at SenseTime’s Lingang intelligent-computing center, where the company claimed a maximum response-accuracy figure of 99.3% and a 9.73% reduction in electricity costs. These are useful indications of what the company wants customers to measure, but they are company and executive claims reported by a media outlet, not independent audits.
The difference is important. An operational result can depend on the starting electricity tariff, the type of workload, the available energy assets, and the details of a local grid program. A percentage improvement in one deployment cannot automatically be applied to every AI data center or industrial user.
The financing nevertheless highlights an emerging part of China’s AI supply chain. Building models and servers draws attention because their outputs are visible. Coordinating the energy that powers those systems is less visible, but it can determine how costly, flexible, and sustainable large-scale deployment becomes.
Damao’s reported round offers a company-level example of that shift. It has raised approximately RMB 200 million, according to multiple financial-media reports, for an AI-energy operations business whose current investors remain undisclosed. The next test will be whether the company can turn its computing-power and electricity coordination tools into repeatable deployments with results that can be independently evaluated.