Dialogue with G7 CEO Zhai Xuehun: The reason for the loss despite revenue of 3 billion is for research and development, and listing is not the main consideration at present

Annie from Wangjing Hyatt
Produced by Quantumbit | Public account QbitAI

G7, an Internet of Things technology company, has continued to be active in the public eye over the past year.

In just over a year, G7 has established a new autonomous driving company, a new asset management company, and raised $320 million in financing during the cold winter. Yesterday (June 25), G7 also announced the establishment of a joint venture with Japan's Marubeni Corporation, "Tianjin Jihong Financial Leasing Co., Ltd.", focusing on cold chain fleet asset services.

This veteran player in IoT technology continues to invest in AI, autonomous driving, and smart equipment. Where does its vitality come from?

How long will this vitality last?

Quantum位 got the answer from G7 CEO Zhai Xuehun.

Where are the barriers?

At present, G7 mainly provides comprehensive fleet management solutions to large logistics companies and freight fleets based on AI and Internet of Things technology platforms, covering the entire fleet operation process including security, settlement, finance, and intelligent equipment.

In addition, G7 and its partners jointly developed an autonomous truck operation network to provide global intelligent equipment and asset operation services to fleets. G7 said that it currently has more than 60,000 customers and more than 1 million connected vehicles.

G7 is engaged in the "asset as a service" business. Customers do not need to purchase logistics vehicles, logistics equipment or even freight after-market services. They only need to rent them on demand and pay for logistics assets based on mileage.

With the development of AI technology and the reduction in the cost of various smart hardware, the entry threshold for purchasing smart devices has been lowered. Can G7's logistics asset-as-a-service model withstand the challenge?

G7 founder Zhai Xuehun believes that G7 has more advantages in such an environment.

He said that G7 is currently mainly engaged in truck (freight) robot networks. The three main parts of the business are not difficult to understand, namely trucks, robots and networks. Regarding these three points, Zhai Xuehun believes that G7 has established barriers.

The network barrier is that the greater the coverage, the stronger the network effect. The first to have 3,000-5,000 cold chain trailers in China has an advantage in cold chain transportation. Robots are also called algorithms. Based on the network, G7's algorithm can prevent the entire system once an accident occurs. Regarding the third point, Zhai Xuehun said that G7 has been cooperating with Tier 1 for a long time, and has many friends and many ways.

Zhai Xuehun believes that the three competitive barriers are indispensable and are most valuable when combined together.

Whoever reaches scale first, has more powerful algorithms, sufficient data and more partners will have the advantage.

Why is the company still losing money with a revenue of 3 billion?

After G7 received $320 million in financing during last year’s so-called “capital winter”, people have been speculating whether G7 will soon go public. In response to this question, G7, which has always kept its revenue secret, also released the latest news.

Zhai Xuehun said that G7's revenue this year has increased sevenfold to more than 3 billion yuan, but it is still non-profitable, but its losses are decreasing every month.

Why is it still in a loss-making state after a revenue of more than 3 billion?

Zhai Xuehun explained that there is no pursuit of short-term profits. At present, the company is still in the stage of investing in technology, and R&D investment accounts for the majority of expenses. While the sales staff is reduced, the R&D team continues to increase its staff.

Regarding G7's future revenue capacity, Zhai Xuehun calmly said that there should be room for revenue growth of ten to twenty times. Regarding the question of whether to go public, Zhai Xuehun responded that this is not the main consideration at present.

At this stage, G7 is based on research and development and technology is king. It wants to occupy the high ground by deepening its technological development.

Two major pitfalls in mass production of truck autonomous driving

As a key technology that can reshape the logistics industry, how autonomous driving can be implemented is a critical issue.

G7 also has plans in this regard. In April last year, G7, Prologis, NIO Capital and Zhongding established the autonomous driving truck company Inceptio Technology.

At present, Yingche's daily operations are carried out by an independent team, and G7's main task is to provide it with data on customer base, landing scenarios and vehicle flow.

So this time, Ma Zheren, President of G7 and CEO of Inceptio Technology, talked about the implementation issues and the two major pitfalls that have not been filled in achieving final mass production.

Ma Zheren summarized the first type of pitfalls as those that autonomous driving technology companies can solve on their own, such as building automotive-grade driverless cars, which is still a challenge at present.

Regarding the improvement of safety performance, Ma Zheren said that actual mass production is very different from laboratory research. Inceptio's solution is also very clear. It is developing an architecture responsible for functional safety, with two main and backup systems with different architectures. The two architectures correct each other to avoid the same mistakes and ensure vehicle safety.

The second category is the current status of the entire autonomous driving industry and the limitations of the external environment. Ma Zheren said that the entire industry is still unclear about the mass production of automotive-grade components.

For example, automotive-grade lidar has a trend towards large-scale mass production, but the specific time plan is still an unknown.

For another example, although there are plans for mass production of automotive-grade autonomous driving chips, we can only hope that they can be priced appropriately and mass-produced on a large scale.

The real implementation of unmanned trucks is not something that can be accomplished by one party alone. The entire industry chain must work together to make further progress. So there is still a long way to go.