AI Unicorn Simo Tech Files with Hong Kong Exchange, Racing to Become "First Stock of Industrial AI Agent"

Amid the narratives comparing to OpenAI, Simo tells a different story

On March 16, Simo Technology officially submitted its listing application to the Hong Kong Stock Exchange, aiming to become the “First Industrial AI Intelligent Entity.”

The listing of Zhipu and MiniMax has sparked a frenzy of reevaluation of AI concepts in the secondary market. But beyond high valuations, the real questions remain: how will it be implemented, and who can turn the story into revenue?

Simo’s answer, as outlined in its prospectus, is: revenue approaching 1.1 billion yuan by 2025, with a gross profit margin rising to 37.3%.

In an industry where most AI companies are still in early commercialization and exploring application scenarios, this financial data presents an alternative path—deep into factories, tackling the dirty, tiring jobs that general models can’t handle, and transforming a series of technical pain points on production lines into real industrial value: 140,000 industrial intelligent entity orders deployed, serving over 730 global clients, completing over 17 billion products with intelligent inspection, and helping Simo become the world’s first company to deploy industrial AI intelligent entities on a large scale, earning the title of China’s largest industrial AI intelligent entity provider.

In a narrative contrasting with OpenAI, Simo tells a different story. Its goal isn’t to create a “Chinese version of ChatGPT,” but to reconstruct the “operating system of global manufacturing” with AI. Will the capital market support this industrial-scale ambition?

Industrial AI Intelligent Entity: A New AI Narrative

As the most representative AI unicorn in the Greater Bay Area, Simo was founded in 2019, when the AI sector was experiencing a boom in capital and startups. Most entrepreneurs chose lower-threshold, faster-to-monetize internet applications and light digitalization scenarios as entry points.

But Simo took a different route: diving into factories, breaking down AI into three core modules—perception, decision-making, and execution—allowing machines, production lines, and even entire factories to continuously improve autonomy and achieve automation and intelligent operations. This full-chain AI technology system for manufacturing is called “Industrial AI Intelligent Entity.”

The core of Simo’s industrial AI intelligent entity is its self-developed, globally first multi-modal industrial large model, IndustryGPT. This model boasts leading understanding of industrial scenarios and strong generalization capabilities. According to public reports, it has achieved SOTA (state-of-the-art) results in multiple standardized professional engineering benchmarks, such as the open-source SuperGPQA industrial subset, outperforming mainstream general large models domestically and internationally. The underlying logic is simple: in vertical scenarios, specialized large models understand the industry better than general models.

Simo’s industrial AI intelligent entity mainly comprises three product lines: robots, edge AI sensors, and intelligent system software, forming a hardware-software integrated ecosystem.

Technological breakthroughs are reflected in specific application scenarios. According to a report by Zhuoshi Consulting, Simo is the world’s first company to achieve 360-degree visual inspection and large-scale commercialization of high-reflectivity, complex surface products; it has also solved core challenges in product recognition and traceability, including successfully cracking invisible QR code recognition on precision optical lenses—core processes that previously relied heavily on manual work, with low efficiency and high error rates—now autonomously handled by machines.

To date, Simo has served over 730 global enterprise clients, including top companies like Tesla and Zeiss, as well as leading Chinese manufacturers such as Luxshare Precision, Goertek, BOE, CRRC, China Innovation Aerospace, and Keda Lili. This indicates that Simo’s industrial AI intelligent entities are deeply embedded in the core supply chains of global manufacturing.

Business Resilience Behind Revenue Structure

Practical deployment has yielded steady results. The prospectus shows that from 2023 to 2025, the company’s revenue will be approximately 485 million yuan, 755.8 million yuan, and 1.086 billion yuan, respectively, with year-on-year growth of 55.9% and 43.7%; gross profit margins for the same period are 30.5%, 32.3%, and 37.3%.

More notably, the company’s adjusted net loss has narrowed each year, from 394 million yuan in 2023 to 379 million yuan in 2024, and further down to 272 million yuan in 2025. This indicates that as revenue scales and operational efficiency improves, the company’s operational quality is significantly enhanced.

Specifically, from 2023 to 2025, revenue from Simo’s industrial intelligent entities accounts for 62.4%, 73.8%, and 78.5% of total revenue, with a compound annual growth rate of 67.8%. In 2025, revenue contributions are approximately 436 million yuan from robots, 342 million yuan from intelligent system software, and 75 million yuan from edge AI sensors. Meanwhile, AI infrastructure contributes about 219 million yuan, maintaining around 20% of total revenue. All major product lines have achieved scaled revenue, indicating that commercialization is not reliant on a single hit but has formed a diversified, replicable product matrix.

Industry insiders note that industrial AI companies typically undergo a lengthy technical validation cycle. Once they establish benchmark clients and standardize products, they enter a phase of “simultaneous growth in revenue scale and gross margin.” From Simo’s financial performance, it’s clear that the company has successfully passed technical validation and is entering a phase of large-scale commercial deployment.

Simo’s commercialization achievements have also received multiple recognitions from the capital market. In mid-2024, Hong Kong Investment Corporation formed a strategic partnership with Simo. Prior to this, the company completed multiple funding rounds, with investors including Cornerstone Capital and Sequoia China. Leading investment institutions and patient capital from the Hong Kong government demonstrate confidence in Simo’s business layout and profitability prospects.

Government policies continue to empower the sector. Earlier this year, the Ministry of Industry and Information Technology and seven other departments jointly issued a document proposing to launch 1,000 high-level industrial intelligent entities by 2027. Recently, the government work report first mentioned “building a new form of intelligent economy,” promoting the rapid adoption of new-generation intelligent terminals and intelligent entities. Continued policy support and implementation are expected to turn industry dividends into broad market opportunities.

Trillion-Scale Challenge for Industrial AI

This opportunity is not limited to China. According to Zhuoshi Consulting, by 2025, more than half of the Fortune Global 500 companies will mainly operate in the industrial sector, which contributes over $28 trillion to global GDP, while existing facilities and labor costs total over $1.5 trillion. This means that industrial AI is not tackling trivial tasks but is instead a massive opportunity for existing infrastructure transformation—who can help factories reduce costs and improve efficiency will share this trillion-dollar pie.

Simo is accelerating its global expansion. From the prospectus, it appears that the company aims to further enhance market penetration by accelerating R&D, optimizing product portfolios, strengthening key customer relationships, and expanding its domestic and international customer base—replicating past successes in more “world factories.”

Currently, industrial AI is shifting from point applications to system-level deployment, with competition focusing on technological systems, scale capabilities, and global deployment. As a “First Industrial Intelligent Entity” aspirant, Simo’s uniqueness is evident: it holds leading market share in multiple segments, maintains top profitability, and benefits from favorable policies, giving it a distinct competitive edge. In a Hong Kong AI sector increasingly valuing “technology implementation and stable cash flow,” Simo avoids the profitability uncertainties of general large models and taps into the trillion-dollar market of global manufacturing digital upgrade.

As “AI + Manufacturing” moves from policy-driven to industry-implemented, Simo’s IPO progress and subsequent market performance will serve as a benchmark: how will the market value a company that “does not chase trends but focuses on factories”? The answer will not only shape Simo’s own capital development but also influence the valuation logic and future direction of the industrial AI sector.