Qianli Technology Backed by Geely: AI Halo Raises Questions About Valuation Substance

Recently, Huaqin Technology (03296.HK) and Shenghong Technology (02476.HK) both landed on the Hong Kong stock market, successfully completing their "A+H" dual-listing strategies and reigniting market enthusiasm for tech companies listing in Hong Kong. Amid this wave, Qianli Technology — backed by the Geely Group — has also attracted significant attention. Bolstered by the AI intelligent driving concept, its valuation has climbed steadily. Yet beneath the AI halo, what is Qianli Technology's true substance?

An 'AI Rising Star' Nurtured by the Geely Ecosystem

Qianli Technology emerged from the vast industrial landscape of Geely Holding Group. Its core business focuses on software and hardware solutions for the intelligent connected vehicle sector, spanning hot segments including smart cockpits, Advanced Driver Assistance Systems (ADAS), and vehicle-road collaboration. Leveraging Geely's rich whole-vehicle resources and application scenarios, Qianli Technology enjoyed innate advantages far exceeding those of peer startups from the very beginning.

In recent years, as AI large-model technologies have accelerated their penetration into autonomous driving, Qianli Technology swiftly repositioned its strategy, adopting "AI + Intelligent Driving" as its core narrative. The company has externally emphasized its deployment in cutting-edge areas such as end-to-end intelligent driving and large-model integration into vehicles. This strategy has proven remarkably effective in the capital market — valuations have continued to rise through multiple funding rounds, with investment institutions scrambling to participate. The AI concept has effectively become the most critical "multiplier factor" in its valuation framework.

Underlying Concerns Behind the Revenue Structure

However, peeling back the glamorous veneer of the AI narrative reveals several issues in Qianli Technology's fundamentals that warrant careful consideration.

First, related-party transactions account for a disproportionately high share. Based on publicly disclosed financial data, orders from internal Geely clients dominate Qianli Technology's operating revenue, with related-party transactions exceeding 70% of total revenue in some reporting periods. This raises questions about the company's business independence — its revenue growth is largely contingent on Geely Group's vehicle sales volumes and internal procurement strategies rather than market-driven competitive capabilities. Should the Geely ecosystem adjust its supply chain strategy or introduce external competing suppliers, Qianli Technology's revenue foundation could be shaken.

Second, the depth of proprietary AI technology remains to be verified. In the intelligent driving domain, true technological moats lie in algorithms, data closed-loop systems, and chip adaptation capabilities. Current industry leaders such as Huawei, Momenta, and Horizon Robotics have all invested massive resources in proprietary algorithm development and large-scale road-testing data accumulation. By comparison, while Qianli Technology frequently references AI and large-model concepts, publicly available information on hard metrics — such as core algorithm research publications, proprietary chip adaptation, and open-road testing mileage — remains relatively limited. The market has legitimate reason to ask: does its AI capability represent deep proprietary technological accumulation, or does it rely more on the integration of third-party technology solutions?

Third, profitability is under pressure. A common challenge across the intelligent driving sector is "heavy investment, long payback cycles." Qianli Technology must sustain high R&D spending to maintain technological competitiveness, yet its revenue side is constrained by the pricing dynamics of related-party transactions and cost pressures from automakers. Across multiple reporting periods, the company's net profit margins have been unremarkable, with some periods even facing losses. While the AI concept has inflated valuations, the sustainability of the profit model remains a lingering question mark.

AI Valuation Bubble or Value Reassessment?

From a broader perspective, the valuation controversy surrounding Qianli Technology actually reflects a widespread phenomenon in the current AI sector — the gap between conceptual premiums and fundamentals.

Since 2024, global capital markets have reached new heights in their pursuit of AI-related targets. From NVIDIA's trillion-dollar market capitalization to sky-high funding rounds for domestic AI unicorns, the letters "AI" alone carry powerful valuation-boosting effects. In the automotive intelligence sector, this effect is particularly pronounced: as long as a company can associate itself with keywords like "end-to-end intelligent driving," "large models in vehicles," or "vehicle-road-cloud integration," its valuation can command a significant premium.

Qianli Technology is a textbook beneficiary of this logic. Backed by Geely's scenario support and order guarantees, combined with AI intelligent driving concept packaging, it has achieved valuation multiples in the primary market far exceeding those of traditional automotive component suppliers. The question, however, is this: when the AI concept tide recedes, investors will inevitably return to scrutinizing a company's core competitiveness — Is the technology truly leading? Is the customer structure healthy? Has the profit model been validated?

Notably, in the Hong Kong stock market, investor tolerance for "concept-driven" companies is declining. Huaqin Technology and Shenghong Technology were able to complete their "A+H" listings smoothly largely thanks to their solid fundamentals and clear paths to profitability. For Qianli Technology, should it choose to list in Hong Kong in the future, demonstrating the "gold content" of its AI story to the more rational Hong Kong investors will be an unavoidable challenge.

Outlook: The Key to Breaking Through Lies in 'De-Geely-ification'

Looking ahead, for Qianli Technology to truly justify its lofty AI valuation, it must achieve breakthroughs in at least the following areas:

First, accelerate external customer expansion. Reducing revenue dependence on the Geely ecosystem and successfully securing mass-production design-win projects from other OEMs is the most direct way to prove market competitiveness. Only when external customer revenue reaches a reasonable proportion will the market recognize its independent revenue-generating capability.

Second, strengthen the AI technology moat. In core technical areas such as end-to-end intelligent driving and large-model deployment, the company needs to deliver quantifiable results — whether in public road-testing data, mass-production delivery scale, or technology patents and academic achievements — all of which will serve as key benchmarks for the capital market to assess its technological strength.

Third, establish a clear profitability timeline. Against the backdrop of industry-wide losses, companies that can be first to validate their business models and achieve stable profitability will hold the initiative in the next round of market consolidation.

In conclusion, Qianli Technology's resource advantages from Geely are undeniable, and the long-term prospects of the AI sector remain promising. But the capital market ultimately returns to the essence of value — conceptual halos cannot forever substitute for performance substance. As the AI wave surges forward, whether Qianli Technology can transition from being "concept-driven" to "value-driven" is an answer that only time will reveal.