Three years of losses totaling 2.2 billion yuan, with executive annual salaries of 400 million yuan. Jia Jiaya's subsidiary Simo Industrial Intelligence's IPO attempt raises doubts.

This newspaper (chinatimes.net.cn) reporter Huang Zhinan Zhang Bei, Shenzhen report

Backed by six years of capital-raising momentum, SmartMore is trying to deliver an “initial capital test” for industrial AI agents in the Hong Kong stock market.

The prospectus disclosed by the Hong Kong Exchanges and Clearing Limited in March shows that industrial AI agent company SmartMore Technology (SmartMore Inc., abbreviated as “SmartMore”), founded by Dr. Jiajia Yao, has formally launched an attempt to list on the Main Board of the Hong Kong stock exchange, seeking to secure the title of “No. 1 industrial AI agent,” and to promote the intelligent transformation of China’s manufacturing industry.

SmartMore was founded in 2019. Including an angel round, it has completed eight rounds of equity financing in succession. Its latest valuation before the IPO was 1.23 billion USD. Behind it, a roster of top-tier institutions has been assembled, including Songhe Capital and the State Lian Securities Innovation Fund (Guolian Zhaozheng Kechuang Fund), among others.

For SmartMore, a Hong Kong IPO is not only a capital-market validation of an industrial AI commercialization story, but also a crucial hurdle to relieve liquidity pressure and break out of the vortex of losses.

As for questions about SmartMore’s profitability and executive compensation, the reporter contacted the company through its official website, but as of the time of publication, no reply had been received.

Six years, eight rounds

SmartMore, which has filed to list in Hong Kong, has topped the industrial AI agent track with a pre-IPO valuation of 1.23 billion USD. Behind the market’s hot pursuit of capital that completed eight rounds of financing in six years, there are persistent losses and liquidity risks lurking beneath the surface—driving divisions in the market over the long-term value of this star start-up.

In 2019, when players such as SenseTime, Megvii, and Yitu were trapped in a red ocean of homogeneous competition in the consumer-grade computer vision track, Dr. Jiajia Yao—then a former professor at The Chinese University of Hong Kong and an internationally top scholar in computer vision—registered and established Hyperspace Group Inc. in the Cayman Islands, the operating entity of SmartMore, placing its entrepreneurial anchor in the industrial AI agent track, which was still in the early stages of commercialization.

Against the industry backdrop in which valuation bubbles had burst and profitability troubles had emerged in the consumer-grade CV track, this more defensible track—with higher technical barriers and more fragmented scenarios—was both a choice for differentiated breakout and a bet on a long commercial cycle.

In its equity structure, Dr. Yao has absolute control over SmartMore. As of the signing of the prospectus, through entities such as Hyperdimension Holdings Limited and Space Travel Management L.P., which are held entirely by Dr. Yao, in total it holds 34.64% of the company’s issued shares, making it the ultimate controller.

This equity structure led by a core technical figure is precisely the core logic behind early capital’s bet: the industrial AI agent track’s strongly tech-driven attributes determine that the technical boundaries of the core team are effectively the product ceiling of the company.

Having been established for six years, SmartMore has completed an end-to-end layout from technology R&D to commercialization, with its core business being the provision of industrial AI agents, covering robot systems, edge AI sensors, and agent software systems. It has achieved scaled deployment across scenarios such as new energy, intelligent manufacturing, and semiconductors.

Among them, industrial AI agents are the absolute revenue pillar. In 2025, revenue from this product line was 853 million yuan, accounting for nearly 80% of total revenue.

However, behind the impressive product roadmap and scenario deployments, the industry’s scaling bottleneck that many industrial AI agent companies face—still remains a key sticking point that SmartMore cannot easily bypass.

In an interview with a reporter from China Times, Dr. Zhang Yi, chief analyst at iMedia Consulting, said plainly that the biggest bottleneck for industrial AI agent companies to achieve large-scale deployment across industries and full scenarios is the dual overlap of (1) the downstream manufacturing industry’s digital maturity and (2) its capacity to adapt technology to standardized requirements—both are indispensable. Of the two, the downstream manufacturing industry’s digital foundation is the prerequisite, while the ability to adapt technology to standards is the key to achieving scaled breakthroughs.

In Dr. Zhang Yi’s view, the weak digital foundation of traditional manufacturing industries directly leads to relatively low willingness to pay for industrial AI agents. This also means there is a lack of motivation to invest in AI technologies and conduct trial-and-error—forming the underlying constraint for cross-industry deployment. Additionally, manufacturing industries differ greatly in process barriers. Even if deployments are made across scenarios, if technology cannot be rapidly standardized and adapted across the entire industry, it will ultimately be difficult to break through the category limitations of high-end manufacturing.

On the commercialization front, SmartMore has turned in a record of high growth. From 2023 to 2025, the company’s total revenue was 485 million yuan, 756 million yuan, and 1,086 million yuan respectively; its compound annual growth rate is close to 50%. In 2025, revenue growth year-on-year reached 43.8%. In the cycle in which domestic demand for industrial intelligence is gradually being released, it has validated its ability to execute on the ground.

However, the quality of this high growth still faces market scrutiny. Regarding the common phenomenon among industrial AI agent companies of “rising volume and prices together but insufficient capacity utilization,” Dr. Zhang Yi pointed out that its essence is high growth driven by customized orders—not growth driven by large-scale demand across the industry. The company’s current growth height depends heavily on customized demands from a small number of top-tier customers, and it has not yet formed a market foundation that supports large-scale mass production. Therefore, the existing trend of “rising volume and prices together” may be difficult to sustain.

He further stated that the high unit price and high income of SmartMore’s robot products come from personalized customized order requests from a handful of top customers. These orders are inherently small in batch size and non-standard in demand, so they naturally do not require the company to release large-scale production capacity—this is also the core reason why similar companies in the industry tend to have low capacity utilization rates.

“Almost half of the capacity is idle; that precisely indicates that besides customized needs from a small number of top customers, there is no large-scale, industry-wide market demand supporting those products. The current growth is not driven by universal industry demand, and the commercial outlook for large-scale mass production has not yet been validated by the market.” Dr. Zhang Yi said.

Customer structure has continued to improve. In 2023, a single customer contributed 15.10% of revenue. In 2024 and 2025, there was no single customer with a revenue share exceeding 10%, and reliance on major customers has significantly decreased. Judging from the business layout, nearly all the company’s non-current assets and earnings come from Mainland China, making it an intelligent enterprise deeply rooted in local industrial manufacturing scenarios.

Strong fundamentals have kept drawing continued capital injections. Since its establishment, including an angel round, SmartMore has completed eight rounds of equity financing in succession. Investors include Hidden Hill Investment, the Guolian Zhaozheng Kechuang Fund, Songhe Capital, Lingchuang Jishi, and other well-known institutions.

Only from August 2024 to February 2026, it issued C-round preferred shares four times, accumulating more than 240 million USD in financing. In the latest round of financing in February 2026, the issue price was 2.32 USD per share, corresponding to a pre-IPO valuation of 1.23 billion USD, making it one of the highest-valued unlisted companies in the industrial AI agent track.

A Hong Kong IPO is a new milestone in SmartMore’s capital-market story. According to the prospectus, the proceeds from this fund-raising will mainly be directed toward core technology R&D, product commercialization expansion, and global market development, aiming to further widen the gap versus competitors.

But what cannot be ignored is that the prospectus has not fully resolved the losses and liquidity pressure that still hover over the company like a sword of Damocles. In the critical period when the industrial AI agent track moves from technical validation to scaled profitability, a high valuation needs continued performance growth and a profitability inflection point to support it—this is the core answer SmartMore will need to deliver to the market in the future.

Risks lurking behind revenue doubling

SmartMore, rushing for the “No. 1 industrial AI agent” title, has presented an impressive performance showing that revenue doubled over three years in its prospectus, but it cannot conceal the ever-expanding loss black hole behind the growth, as well as the liquidity crisis hidden deep within the balance sheet.

According to the prospectus data, SmartMore’s revenue increased from 485 million yuan in 2023 to 1,086 million yuan in 2025, achieving a doubling over three years. Yet it failed to reverse the loss situation. In the same period, net losses were 546 million yuan, 735 million yuan, and 991 million yuan respectively; cumulative losses over three years exceeded 2.27 billion yuan.

Even after stripping out non-operating items such as changes in fair value of preferred shares and share-based compensation, the core business still did not achieve profitability. In the same period, operating losses were 427 million yuan, 425 million yuan, and 769 million yuan respectively, with the loss magnitude widening year by year.

Regarding this performance of “revenue doubling while losses also expanding,” Dr. Zhang Yi analyzed for this reporter that the predicament of “gross profit cannot cover expenses” is the combined result of both common industry features in industrial intelligence development and the company’s own operating deviations. The high R&D investment in the industry’s 0-to-1 stage is a shared characteristic, but SmartMore’s loss amplification mainly stems from an internal imbalance in expense control and an overly aggressive operating strategy—not an inevitable outcome of industry development.

He further explained that SmartMore’s equity incentive plans and administrative expenses were excessive. In 2025, operating expenses exceeded revenue for the period. In essence, this is a severe imbalance in expense control, compounded by an overly aggressive overall operating strategy, directly causing the scale of losses to expand. This problem is not a necessary result of industry development, and it also reflects insufficient efficiency in the use of the company’s operating funds.

The core driver behind the expanding losses comes from a large-scale equity incentive operation just before the IPO. SmartMore launched two equity incentive plans in 2022 and 2025 respectively. From 2023 to 2025, the share-based payment expenses recognized by the company were 15.661 million yuan, 33.272 million yuan, and 475 million yuan respectively. Among these, in 2025 this item surged 1,328% year-on-year, directly absorbing nearly half of the revenue for the period.

The core source of this expense is a policy of accelerated vesting of 30.36 million unvested shares held by management. In December 2025, SmartMore applied accelerated vesting for 30.36 million shares held by the management team that had not yet vested, and it recognized a one-time 336 million yuan share-based payment expense, making it the most direct reason for the jump in losses in that period.

Corresponding to the massive equity incentives is a compensation level that severely diverges from the underlying business fundamentals between the management team and SmartMore. In 2025, the annual compensation for executive directors Lü Jiangbo, Li Ruiyu, and Liu Shu was 104 million yuan, 138 million yuan, and 163 million yuan respectively; the three together received more than 405 million yuan. Among this, the overwhelming majority came from equity incentive-related compensation.

Even for founder and board chairman Jiajia Yao, compensation in the same period reached 1.887 million yuan. For a company whose annual revenue had just surpassed 1 billion yuan but remained deeply in losses, such high management compensation has already become a core focus of controversy in the market.

In response to market controversy triggered by the massive equity incentives just before the IPO, Dr. Zhang Yi said that equity incentives centered on share-based payments are the mainstream necessary tool in the industry for binding the core team for an unprofitable hard-tech company; however, the scale of SmartMore’s equity incentives this time is seriously out of balance with the company’s loss-making situation and tight cash-flow condition. The operating boundary is blurred, raising suspicions of harming the interests of small and medium shareholders and engaging in benefit transfers.

“The core team is the core asset of a hard-tech company. In the entrepreneurial stage where the company has not yet turned profitable, cash flow is highly constrained, and the space for cash incentives is extremely limited, equity incentives centered on share-based payments are a necessary method to bind core talent, and they are also a mainstream operating approach in the industry.” Dr. Zhang Yi said directly. However, in the context of SmartMore’s net loss of nearly 1 billion yuan in 2025 and highly tight cash flow, even share-based payment expenses issued only to the management team exceeded 400 million yuan, representing a proportion of the period’s administrative expenses that is significantly higher than normal industry levels. This can no longer be explained solely as “binding core talent.”

In his view, when a company is suffering massive losses and cash flow is under pressure, issuing large-scale share-based payments to core management directly increases administrative expenses and enlarges the company’s losses. From the perspective of corporate governance, there is a possibility of harming the interests of small and medium shareholders.

Beyond the one-off impact of equity incentives, the double-high investment model in the industrial AI agent track is the underlying reason SmartMore cannot get out of the loss cycle.

From 2023 to 2025, its employee welfare expenses were 336 million yuan, 300 million yuan, and 737 million yuan respectively, with compensation for R&D personnel accounting for more than 60%. Sales and marketing expenses were 160 million yuan, 236 million yuan, and 400 million yuan respectively, with a compound annual growth rate of 58%, far exceeding the revenue growth rate over the same period.

More worrisome than continuous losses is the huge preferred-share liability on the balance sheet and the fatal liquidity risk it brings.

Because each round of preferred shares issued comes with the right to convert at any time and there are no redemption clauses completed after the IPO, according to International Financial Reporting Standards, these preferred shares are classified entirely as current financial liabilities. By the end of 2025, SmartMore’s preferred shares and related financial liabilities had a carrying balance of 4.23 billion yuan, accounting for nearly 80% of total liabilities.

This liability directly causes its financial structure to deteriorate continuously. By the end of 2025, total current liabilities were 5.293 billion yuan, while current assets were only 1.954 billion yuan. Current liabilities exceeded current assets by 3.339 billion yuan. The asset-liability ratio was as high as 256.9%, and net liabilities totaled 3.258 billion yuan.

Although SmartMore emphasizes that preferred shares will automatically convert after a qualified IPO is completed, with no cash-out pressure, if the Hong Kong listing is not completed before August 28, 2029, preferred shareholders have the right to demand redemption of all shares at 100% of the issue price plus a 10% compounded annual interest rate. At that time, there will be a massive cash redemption pressure.

Continuous “bleeding” of operating cash flow further amplifies liquidity risk. From 2023 to 2025, SmartMore’s net cash outflows from operating activities were 372 million yuan, 424 million yuan, and 327 million yuan respectively. Over three years, the cumulative net outflow exceeded 1.123 billion yuan. Daily operations rely entirely on financing to replenish cash.

In the same period, the net cash inflows from financing activities were 7.197 million yuan, 558 million yuan, and 656 million yuan respectively. By the end of 2025, the balance of cash and cash equivalents was 949 million yuan. If operating cash flow cannot turn positive in the short term, the company’s existing cash reserves can only support less than three years of operations.

In addition, factors such as the risk of collecting accounts receivable, intensifying industry competition, and changes in tax incentives also add uncertainty to the company’s subsequent operations. The long-term value of the industrial AI agent track is beyond doubt, but in capital markets the valuation ultimately anchors to the company’s profitability ability and the health of its cash flows.

For SmartMore, an IPO is only the starting point of its capital-market journey. How to maintain revenue growth while also achieving cost control, narrowing losses, and turning operating cash flow positive—that is the core answer it must deliver to the market.

Editor: Zhang Bei Chief editor: Zhang Yuning

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