Recently, SenseTime announced the completion of a new share placement of approximately 2.5 billion HKD, attracting market attention not for the scale of financing, but for its clear use of funds—the announcement explicitly states that about 20% (nearly 500 million HKD) will be used to promote its RWA (real-world assets) and stablecoin-related business development.
Once the news broke, the industry was in an uproar. This move posed a sharper question for the entire industry: 'After the Hundred Models War', when the traditional SaaS charging model can no longer support huge R&D investments, how can AI companies truly make money?
For SenseTime, which has accumulated losses of hundreds of billions and is in the core battlefield, is this a helpless move under financial pressure, or a far-reaching layout aimed at revitalizing core assets? SenseTime's RWA strategy may be the answer to this question. It reveals a brand new path: deeply embedding AI capabilities into finance, transforming the company from a 'technology service provider' to an 'asset creator'. This is not only SenseTime's self-rescue but may also be a common chess game for future AI giants.
From the core contradiction in the financial report, RWA is a financial breakthrough under the 'good reputation but poor performance' reality.
Why is SenseTime embracing RWA? The company's financial statements provide an answer: they clearly present a harsh reality of 'good reputation but poor performance'.
Although in 2023, the income from the generative AI business reached 120 million RMB, with a year-on-year growth of as high as 200%, becoming the fastest-growing new business segment in the company's ten-year history, the net loss attributable to the parent company still reached 6.495 billion RMB that year.
From 2018 to 2023, SenseTime's cumulative losses have reached 50.324 billion RMB, and if we add the 2.477 billion RMB loss in the first half of 2024, the total accumulated loss has soared to 52.8 billion RMB. This continuous and massive loss sharply contrasts with the company's significant technological progress and market share in the generative AI field.
The root of this contradiction lies in the high R&D investment and relatively slow commercialization progress. From 2018 to the first half of 2024, SenseTime's cumulative investment in R&D expenses has reached 18.205 billion RMB. Although the explosive growth of the generative AI business and the surge in model invocation indicate the strong potential of the technology, the traditional SaaS charging model (model as a service) is still 'very far' from achieving profitability in core business. Facing a market value of up to 39.359 billion HKD, compared to its peak market value of 320 billion HKD, only a fraction remains, and the management must seek a new model that can rapidly monetize huge technological investments to improve cash flow and reduce losses.
RWA provides SenseTime with a potential path to break through the limitations of the traditional SaaS model by 'normalizing' expected returns, allowing for rapid recouping of technological investments and revitalizing assets.
SenseCore: From cost center to tokenizable 'heavenly selected strategy'
SenseTime's SenseCore AI** device is its core technological moat and also its largest cost center.** Since around 2018, SenseTime has invested billions annually to build its computing power infrastructure, including the AIDC smart computing center in Shanghai Lingang, and continues to expand computing nodes in Guangzhou, Shenzhen, and other places, forming a scarce large model infrastructure in the country. As of 2023, the total computing power scale of SenseTime's large device has exceeded 12,000 petaFLOPS, with the number of GPUs online reaching as high as 45,000 cards. By 2024, its computing power has increased to 23,000 Petaflops, a year-on-year growth of 92%.
Such a massive investment in computing power has led to remarkable improvements in model training and inference efficiency. For instance, SenseCore can achieve a 600% increase in large model inference efficiency and a 90% reduction in incremental training costs. However, the costs of building and maintaining these heavy assets are enormous, and they are not fully utilized, leading to significant cost burdens.
RWA provides the 'heavenly selected strategy' to solve this core contradiction: transforming huge computing costs into tradable, financeable, and profitable financial assets through 'computing power tokenization'. Computing power assets (such as GPU hardware) are considered ideal RWA anchor assets due to the 'rigid demand' of the AI industry and trusted 'digital genes'. Through Web3 technology, SenseTime can digitize physical devices (computing power) and realize immediate monetization of expected returns. This model can not only activate the massive fixed assets tied up in SenseCore but also provide new financing channels for its continuous expansion of computing power and technological iteration, fundamentally reshaping the valuation logic of its heavy asset operations.
From visual AI to multi-modal, a unique 'entry ticket' into RWA after technological sedimentation.
SenseTime's strategic transformation from visual AI to generative AI has accumulated a unique technological 'entry ticket' for its entry into the RWA field.
Before going public in 2021, SenseTime was the largest computer vision software company in China, with business covering smart business, smart cities, smart cars, and smart living. Over the past decade, SenseTime's deep accumulation in perceptual intelligence and decision intelligence, as well as its reserves of massive multi-modal data, have strengthened its foundational models' understanding of the physical world and multi-modal capabilities. For example, SenseTime's SenseNova large model system has achieved domestic leading levels in various aspects such as foundational models, multi-modal, programming and tool invocation, and lossless context of millions of words.
The value anchoring and liquidity management of RWA often require precise evaluation of complex assets, which cannot be achieved without the fusion analysis of various heterogeneous data such as satellite remote sensing data, IoT sensor data, and text information. SenseTime's extensive applications and data accumulation in remote sensing interpretation, smart city management (such as urban services, emergency response), smart cars (SenseAuto), smart mobile terminals (SenseME), and the financial sector (in partnership with China Merchants Bank, Haitong Securities, etc.) enable it to handle and understand these complex multi-modal data.
AI technology can automatically identify and evaluate traditionally hard-to-evaluate assets through multi-source data fusion and dynamic valuation, generating accurate dynamic valuation models. Additionally, AI plays a key role in cross-border data compliance reviews, achieving real-time compliance checks through intelligent identification, dynamic monitoring, and risk assessments, further reducing the compliance risks of RWA projects. These technological capabilities empower SenseTime to participate deeply in the RWA market by providing solid technological foundations for the issuance, pricing, liquidity management, and compliance of RWA.
In summary, SenseTime's embrace of RWA is a strategic necessity under financial pressure, seeking to monetize its core asset (SenseCore computing power) and reshape its valuation logic. The explosive growth of its generative AI field, coupled with persistent losses, and the operational pressure of SenseCore as a heavy asset, compel it to explore new profit models that can directly convert technological investments into financial assets. Meanwhile, SenseTime's long-standing deep technological accumulation in visual AI and multi-modal data processing provides it with a unique technological advantage for digitalizing, valuing, and circulating complex real assets in the RWA field. Therefore, laying out RWA is not just an embellishment for SenseTime but a 'financial self-rescue' crucial to its future survival and development.
The 'AI + RWA' value architecture as the core competitive advantage of the enterprise
SenseTime's real moat is not isolated from its outstanding AI technology, but lies in the complete closed loop it has built to engineer, productize, and ultimately financialize cutting-edge AI capabilities. This unique 'AI + RWA' strategic approach enables it to potentially play the triple roles of 'value discoverer, risk estimator, and asset creator' in the real-world asset (RWA) field, thereby breaking through the traditional business model of technology services and opening up new space for value growth.
Regulatory uncertainty is also a potential challenge. Hong Kong's policies are relatively open, but there are still differences compared to the US's strict delineation of asset nature and securities boundaries. Companies and investors need to pay attention to the long-term game between regulatory attitudes and market outcomes.
Activating dormant physical assets
The first step in SenseTime's strategy is to utilize its multi-modal AI capabilities to accurately assess the value of physical assets that are difficult to penetrate within the traditional financial system. Its 'Daily New SenseNova' large model system, with its powerful ability to process cross-modal information such as language, images, and time-series data, provides a unique solution for this.
A typical application scenario is to conduct asset value assessments for palm oil plantations in emerging markets such as Southeast Asia. These assets often face challenges in obtaining traditional credit support due to remote geographical locations and lack of financial data. SenseTime's AI valuation model can break through this bottleneck by transforming the future revenue rights of plantations into investable RWA products. The model will integrate a complex data matrix: leveraging SenseEarth's intelligent remote sensing capabilities to analyze vegetation health and climate patterns through high-resolution satellite images to predict yield; combining IoT sensors deployed in fields to monitor key production factors such as soil and environment in real-time; and utilizing SenseChat's natural language processing capabilities to deeply analyze global trade reports and market futures prices.
In this way, 'Daily New' can transform vast amounts of unstructured data into dynamic, credible valuation models that reflect the intrinsic value and potential risks of assets in real-time. This not only opens up innovative financing channels for traditionally hard-to-standardize and liquid agricultural assets but more importantly, demonstrates AI's core ability as a 'value discoverer'—to make dormant data speak and reveal the value of invisible assets.
Creating a native category of digital assets
After proving its value discovery capabilities, SenseTime's strategy naturally evolves to the second stage: shifting from assessing existing assets to creating entirely new native digital assets. Its industry-leading AIGC tools, such as the image generation model 'Quick Paint SenseMirage' and multi-modal short film creation tool 'Seko', lay a solid foundation for this.
A highly forward-looking business concept is that SenseTime can build a 'SenseDrama AI Creation Platform' to empower creators to generate AIGC short dramas at low cost and high efficiency. The platform not only provides creative tools but also integrates AI evaluation models to select high-commercial-potential quality content from a vast number of works. Subsequently, the future revenue rights of these selected short dramas (such as advertising revenue sharing, copyright sales, etc.) will be packaged and tokenized, becoming a new type of RWA product for global investors.
The strategic significance of this move lies in its unprecedented depth of integration between content creation and financial markets. SenseTime's role transforms from a technology service provider to a 'generator' and 'enabler' of digital assets. The company no longer solely relies on the slow software-as-a-service (SaaS) charging model but can directly benefit from the value growth of digital content assets generated by its technology. This not only achieves the direct capitalization of technological investments but also provides a new financing paradigm for the entire creative industry.
Activating computing power infrastructure
The third step of the strategy, and the most profound one, is to turn its attention inward and financially transform its core and heaviest asset—SenseCore AI large device. The vast computing power cluster with tens of thousands of GPUs is not only the cornerstone of SenseTime's technological leadership but also a heavy asset on its financial statements. Tokenizing it is a strategic move to address this challenge.
By issuing 'SenseCore Compute Token (SCT)', SenseTime can convert standardized computing rights (e.g., 'one hour of A100 GPU inference power') into a financial product that can circulate on compliant digital asset trading platforms. The pricing of SCT will be dynamically adjusted by market supply and demand, electricity costs, and equipment depreciation through algorithms. For SenseTime, pre-selling SCT can monetize future computing services in advance, obtaining valuable cash flow to support R&D and expansion. For the market, it significantly lowers the threshold for small and medium-sized enterprises to use top AI computing power, promoting the inclusivity of AI technology.
This initiative marks the transformation of SenseTime's business model from a cost center to a profit center. It not only revitalizes massive fixed asset investments but more importantly, achieves the most efficient allocation of computing power resources through a market-oriented trading mechanism, directly converting the company's engineering capabilities into highly liquid financial assets.
It can be seen that SenseTime's moat is not a single technological node, but a carefully constructed complete value chain of 'engineering-product-finance'. SenseCore's engineering capability builds the underlying infrastructure, the productization capability of the SenseNova family transforms technology into applications, and the financialization capability of 'AI + RWA' is key to achieving value leap.
This strategic closed loop allows SenseTime to perfectly play three core roles in the RWA era:
Value discoverer: Using AI to penetrate the information fog and price dormant assets in the physical world.
Asset creator: Utilizing AIGC to create native assets in the digital world and financializing their revenue rights.
Risk price estimator: Providing accurate risk assessments for the above two types of assets through real-time data and dynamic models.
Through this interconnected strategic framework, SenseTime Technology not only hopes to address current financial challenges but may also reshape its valuation logic, evolving from a leading AI software company to an indispensable asset value creation and trading platform in the next generation of the digital economy.
What does the future hold? A simple execution path and risk deduction.
Although this path has broad prospects, its success depends on whether the company can clearly recognize and navigate a series of profound internal challenges and external compliance requirements. This is not merely a business expansion but a comprehensive test of strategic determination, organizational capability, and market trust.
Core challenge: Strategic balance between focus and opportunity
The core challenge currently faced by SenseTime arises from the inherent tension between its identity as an AI leader and the financial attributes of RWA.
The company is fully engaged in the core battlefield of the 'Hundred Models War', and its 'Daily New' large model system is in a critical window of rapid iteration, where any deviation of resources could incur high opportunity costs. Against this backdrop, investing capital and elite teams into the new field of RWA must be carefully weighed against its potential dilution effect on the main business. This is not only a matter of fund allocation but also a pull on organizational energy.
A deeper challenge lies in expanding the boundaries of capability. SenseTime's proud AI research strength and the financial, legal, and compliance expertise required by RWA belong to different fields. Building an RWA product requires compliant officers who have a deep understanding of the regulatory framework of the Hong Kong Securities and Futures Commission, experts skilled in financial product structure design, and experienced licensed leaders. This lack of 'financial genes' cannot be simply compensated through technological advantages in the short term; it constitutes the most realistic gap between technological concepts and compliant products.
Ultimately, all challenges will converge on one fundamental question: trust. When AI models are used as the core for pricing hundreds of millions of dollars in assets, their reliability becomes the ultimate concern for the market.
The 'illusion' risk of AI and the 'black box' nature of decision-making processes inherently contradict the principles of transparency, explainability, and auditability required in the financial field. Therefore, SenseTime must not only prove the advanced nature of its AI technology but also build a mechanism that allows the market, investors, and regulators to trust the fairness and robustness of its 'AI oracle'.
This requires the co-evolution of technology and制度, such as integrating its AI models with decentralized oracles like Chainlink, introducing third-party independent audits, and actively embracing the regulatory sandbox of the Hong Kong Monetary Authority for pilot trials, gradually building market confidence through transparent practices.
Realistic path: A cautious start leveraging Hong Kong's ecosystem.
Given SenseTime's reality of 'strong technology, tight capital, and no financial licenses', attempting to independently apply for financial licenses such as Virtual Asset Service Provider (VASP) is undoubtedly a long and uncertain road. A more pragmatic and risk-controllable initial path is to choose to become a 'technology enabler' in Hong Kong's mature financial ecosystem, rather than a direct financial participant.
The most feasible strategy is to establish deep cooperation with local licensed institutions, such as forming joint ventures or establishing strategic partnerships. By teaming up with financial institutions or virtual asset platforms that hold relevant licenses, SenseTime can cleverly circumvent licensing barriers, leveraging partners' compliance systems and professional talents to compensate for its shortcomings in financial operations. The cooperation between Ant Group and Hong Kong Victory Securities has already provided a successful example of such a model.
In this process, the role of strategic investor Infini Capital is crucial. As an investment institution focused on Web3, its value goes far beyond financial support. It should be seen as the 'guide' and 'catalyst' for SenseTime's entry into Hong Kong's Web3 and financial ecosystem, capable of introducing key partners and providing deep industry insights for its strategy. This cooperation model allows SenseTime to focus on its core strengths—providing top-notch AI technology solutions, such as asset valuation models, risk assessment engines, and smart contract auditing tools, thereby entering the core aspects of the RWA value chain while avoiding direct regulatory friction.
From enabler to infrastructure evolution
Based on the above analysis, SenseTime's RWA strategy should be gradual, verifying its maximum value with minimal risk.
The first step should focus on launching a benchmark project for 'AI-powered RWA Asset Assessment as a Service (Valuation-as-a-Service)'. SenseTime should collaborate with a local licensed asset management or assessment institution to provide its AI dynamic valuation and risk monitoring models for asset categories with high data availability and established compliance practices, such as new energy facilities, logistics assets, or carbon credits. In this model, SenseTime, as a pure technology service provider, outputs API interfaces or software services to assist partners in enhancing the efficiency and accuracy of asset assessments. The brilliance of this strategy lies in its ability to fully showcase the unique value of its multi-modal AI in a controllable risk real-world scenario while gradually establishing market trust in its AI models' reliability, laying the foundation for deeper participation in the future.
In the long-term vision, SenseTime should strive to become an 'AI infrastructure provider' in the field of RWA. This positioning is consistent with the company's core strategy of 'large devices-large models-applications' and is a natural extension of its 'AI-as-a-Service' concept in the fintech field. Just as Amazon AWS became the underlying infrastructure of the internet era, SenseTime's ultimate goal is to provide foundational AI valuation, risk control, compliance review, and intelligent matching services for the entire RWA ecosystem.
This evolutionary path starts from the initial asset assessment service, gradually expanding to AI-driven compliance and auditing services, and finally to intelligent trading and liquidity optimization solutions, ultimately forming an RWA-specific AI Agent platform. This road not only has vast market space but, more importantly, allows SenseTime to maximize the reuse value of its technology while always standing on the fundamental basis of its technology company, building an insurmountable moat in the next generation of the digital financial ecosystem in a low regulatory risk model.
Author: Zhao Qirui, Reviewed by: Zhao Yidan