Frontier | Path Selection After AI Revenue Exceeds 100 Million: Weimob's Implementation of the AI First Strategy and Challenges in B2B Delivery

Text by | Zhang Ziyi

Edited by | Yuan Silai

Against the backdrop of the SaaS industry generally facing growth bottlenecks and seeking digital and intelligent transformation, Weimob held a city summit at its Shanghai headquarters on April 22, 2026, officially presenting its "AI First" strategy panorama to the public.

According to Weimob's 2025 financial report, its AI-related business revenue has exceeded 100 million yuan for the first time, and the quarter-on-quarter growth rate in the second half of 2025 reached 130%. Based on these financial data, Weimob attempts to elevate AI from its original position as a product auxiliary plugin to the height of a business foundation through strategic upgrading.

The core of Weimob's "AI First" strategy proposed this time covers directions such as AI + SaaS, AI + marketing, AI + going global, and AI To C.

At the technical architecture level, Weimob has upgraded it to "Agent + Skills". The underlying logic of this transformation is to encapsulate the originally complex SaaS system functions (Skills) into a more interactive form, which is called by the intelligent agent (Agent), thereby reducing the threshold for merchants to operate complex systems.

You Fengchun, Executive Director and Group President of Weimob Group, said that AI is evolving from simple dialogue interaction to autonomous execution.

Currently, this logic has been tried and implemented in Weimob's "Crayfish" ecosystem and other businesses. For example, merchants no longer need to search for data through multi-level menus in the background, but can directly retrieve the daily transaction volume through dialogue. This leap from "point-like functions" to "systematic empowerment" is the beginning of Weimob's attempt to reconstruct the underlying logic of business.

However, when promoting this grand strategy to actual business scenarios, SaaS manufacturers must face a harsh reality: the B2B business has much higher requirements for the certainty of technology than the B2C business.

Although everyone at the consumer end can use AI, in terms of actual application, B2B customers have much stricter requirements and needs than B2C customers.

Xiao Feng, Vice President of Technology at Weimob, pointed out that C2C users have a relatively high psychological tolerance for the illusions of AI. If an AI tool makes mistakes when answering common-sense questions, C2C users usually only think that the product is "not smart enough" and try to adjust the way of asking questions. But B2B customers are paying users, and every action of AI is directly related to the business scenario and financial results.

"As long as there is one bad case, B2B customers will think that the entire AI module is unusable." Xiao Feng gave an example to illustrate this difference: in the AI virtual fitting scenario, if the model's photo shows the model leaning against the wall or holding a heavy object, the recognition effect will be affected. For C2C users, after the customer service explains, users are usually willing to cooperate and change the pose; but B2B merchants will directly question the technical efficiency and refuse to pay. This almost "zero tolerance" requirement for stability determines that when Weimob promotes the AI First strategy, it must invest more R & D resources in safety checks and scenario adaptation, rather than blindly pursuing gorgeous technical indicators.

Based on this prudent consideration, when Weimob launched functions such as Weimob Admin Skill for the Crayfish ecosystem, it first focused on the safety check mechanism. Its purpose is not to cash in quickly, but to solve the operational stability problem of merchants in the business scenario by encapsulating the original API, and gradually build the trust of B2B users in AI through a "smooth feeling".

This pursuit of "certainty" and "stability" also directly affects Weimob's expansion rhythm in emerging business fields.

Take the recently launched GEO (Generative Engine Optimization) solution "Xingqi" as an example. As AI search gradually reconstructs the way users obtain information, how to make brand information more visible in AI answers has become a new opportunity for the marketing business.

But in Xiao Feng's view, the GEO technology itself is not difficult. The difficulty lies in how to maintain compliance in the rapidly changing traffic dividends. He revealed that Weimob has established an extremely strict review mechanism for the GEO business internally: each order needs to go through three rounds of review, and the last round is controlled by the legal department.

Xiao Feng clearly stated that Weimob has rejected products with high budgets but involving pyramid schemes or compliance risks. This "restraint" in the face of business opportunities reflects the underlying logic of B2B AI service providers - in the technological transformation period, protecting the health and sustainability of the business is more important than short-term revenue explosion.

Currently, many products, including GEO and AI Work365, are derived from Weimob's internal innovation center mechanism. This mechanism encourages employees to incubate AI-native applications with market prospects and make small and fast attempts within the institutional framework.

While exploring business externally, Weimob's internal R & D management model is also adapting to the AI First strategy. In the code writing process, Weimob has introduced AI-assisted programming, but Xiao Feng emphasized that the current AI is still unable to independently undertake large-scale, cross-module development tasks.

To ensure the stability of the underlying business, Weimob will choose a gradual approach of fragmentary generation to ensure that the technical foundation is not affected during the transformation process.

Judging from the financial performance, the fact that Weimob's AI revenue has exceeded 100 million yuan means that the integration of AI in the SaaS business has been initially verified by the market. However, the leap from an "auxiliary tool" to a "business engine" means that Weimob needs to handle more complex B2B delivery relationships.

In the future, Weimob's performance under the AI First strategy will largely depend on whether it can find the optimal balance between the extremely high quality requirements of B2B customers and the boundaries of AI technology.