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DeepExi CEO Reveals Strategy to Win China's ToB Market with Flagship Clients and Intelligent Systems

Summarized by NextFin AI
  • Zhao Jiehui, CEO of DeepExi, highlighted that success in China's B2B market requires deep engagement with flagship clients and leveraging their feedback for product iteration.
  • During the 2025 T-EDGE, Zhao emphasized that sustainable revenue growth depends on being the go-to advisor for clients, necessitating in-house talent with R&D expertise.
  • He described intelligent systems as complete ecosystems that excel in processing specific data, training models, and integrating into workflows.
  • Zhao stated that creating customer value through technological advancement is the first principle of ToB business, even under high service investment and margin pressure.

Zhao Jiehui, Founder and CEO of DeepExi, emphasized that success in China's B2B market depends on deep engagement with flagship clients, leveraging their feedback to iterate products, and building intelligent systems that enhance or replace key business functions.

Zhao elaborated on intelligent system with Jany Hejuan Zhao, the founder and CEO of NextFin.AI, during the 2025 T-EDGE. The annual feast of ideas brings top scientists, entrepreneurs and investors to address the pressing issues of the AI era, which kicked off globally on December 8 and runs through December 21.    

Drawing parallels to Palantir's success, Zhao said the key lies in "building flagship clients to establish industry influence, providing deep services to top-tier customers, and using client feedback to iterate products and services."

He described this model as "trading depth for barriers and leveraging benchmark clients to build an ecosystem," which aligns closely with the underlying logic of China's B2B market.

According to Zhao, sustainable revenue and gross margin growth in the ToB market depends on becoming the go-to advisor for clients. Companies must stay a step ahead of their clients in technological iteration, service quality, and industry insight. This capability, Zhao noted, cannot be outsourced—it requires in-house talent with both R&D expertise and business acumen, a rare and highly sought-after skill set that must be cultivated internally.

Zhao stressed that true intelligent systems are not standalone models or tools, but complete ecosystems capable of replacing or augmenting specific roles. Such systems must excel in three core areas: processing scenario-specific data, training models based on that data, and seamlessly integrating models into existing workflows.

He emphasized that the first principle of ToB business is creating customer value through technological advancement. Even when service investments are high and margins are under pressure, companies should not deviate from this principle. Instead, Zhao said, firms should leverage visualized operations, product iteration, and upgraded service capabilities to transform labor-intensive tasks into high-margin offerings.

"The key is continuously abstracting generalizable capabilities and productizing pain points discovered during service delivery," Zhao added.

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Insights

What are intelligent systems in the context of B2B markets?

What strategies did DeepExi's CEO emphasize for success in China's B2B market?

How does client feedback influence product iteration at DeepExi?

What parallels can be drawn between DeepExi and Palantir in terms of business strategy?

What are the current trends in China's ToB market according to Zhao Jiehui?

What recent updates were discussed during the 2025 T-EDGE event?

What challenges do companies face when building intelligent systems?

How must companies adapt to become the go-to advisor for clients in the ToB market?

What role does in-house talent play in DeepExi's business strategy?

What is the significance of flagship clients in DeepExi's ecosystem model?

How can companies leverage technological advancements to create customer value?

What are the long-term impacts of intelligent systems on labor-intensive tasks?

What limitations exist in outsourcing the development of intelligent systems?

What historical cases illustrate the success of deep client engagement in B2B markets?

How does DeepExi's approach compare to traditional B2B service models?

What are the core areas where intelligent systems must excel to be effective?

How has the feedback from top-tier customers shaped DeepExi's offerings?

What insights did Zhao provide regarding industry influence in the B2B market?

What is the future outlook for intelligent systems in enhancing business functions?

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