There is a shortage of practical scenarios for K12 AI learning, a long-standing disconnect between learning content and practical application in higher education, and a common dilemma that working people cannot take on real business orders after finishing relevant courses. Jianghu Wanxiang applies the closed-loop model of "learn - create - earn" to cover users across the entire lifecycle.

Learn — Create — Earn: Jianghu Wanxiang Builds a Profit-Making Closed Loop for AI Capabilities With a Xianxia Worldview

From K12 to the workplace, enabling continuous growth and monetization of AI capabilities, Jianghu Wanxiang is seeking angel round financing.

Under the wave of AI technology implementation and application, a repeatedly verified gap is emerging: ordinary people "cannot learn AI capabilities well, cannot apply them properly, and cannot make money from them". This gap does not only exist in a specific group of people, but covers the full cycle of K12 teenagers, college students and workplace professionals. Children consume AI through short videos and AI toys, but rarely have the opportunity to give full play to their creative talents and produce deliverable works with AI; there is a practical training gap between college courses and the actual needs of the industry, and students face a capability gap immediately after graduation; even if workplace professionals and freelancers have mastered prompt tools, they lack an outlet to turn "being able to do things" into "order receiving, delivery and payment collection". Recently, Anhui Xiaoxianbao Technology, which has been deeply engaged in the AI application field for 9 years, has officially launched a platform-level product — Jianghu Wanxiang AI Digital Creation Platform. By covering the full-cycle growth path from K12 teenagers, college youth to workplace professionals, it opens up the complete closed loop of "learning - practice - creation - earning", and fills the systematic gap in the current AI talent training field.

I. Starting from the pain point of "cannot learn well, cannot apply properly, cannot make money", Jianghu Wanxiang builds AI capability cultivation into a closed loop

Jianghu Wanxiang is an AI digital creation platform run through by a xianxia worldview, which connects AI capability cultivation, creative tools, real order transactions and personal growth data assets through the closed loop of "learning — practice — creation — earning". The product consists of three versions: Lingya (Youth Version) for teenagers aged 9-17, Yuanshenjie (University Version) for college students, and Jianghu Wanxiang (General Version) for workplace professionals and freelancers. The three versions share the same account system, the same worldview and the same set of data assets. Users enter from the K12 stage, and their growth path can extend to the workplace.

The reason why the team chose the "learn — create — earn" closed loop instead of general tools or pure courses stems from nine years of industrial practice. Anhui Xiaoxianbao Technology was founded in 2017. In the early stage, it entered the AI hardware track and participated in the research and development of the world's first artificial intelligence headset; then it applied AI technology to cross-border e-commerce, operated the Xingchao cross-border brand and cross-border e-commerce industrial park, and accumulated experience in talent training and early OPC community operation. This experience made the team repeatedly observe that the bottleneck of AI capabilities does not lie in the model layer, but in the lack of systematic support in the link from "learning to use" to "receiving orders". Jianghu Wanxiang just turns this link into a product, uses xianxia narrative to lower the cognitive threshold, and extends "being able to use AI" to "making money with AI" through closed-loop design.

II. Four self-developed engines + Avatar Internet form the core capability that distinguishes it from general tools

In terms of technical architecture, Jianghu Wanxiang builds differentiation around a three-layer self-developed system. The bottom layer consists of four self-developed engines: the "Wanxiang Lingxi" demand disassembly and completion engine, which automatically disassembles and completes vague demands put forward by users or institutions into executable tasks; the "Wanxiang Yunjian" task vector matching engine, which performs two-way vector matching between demands and supply-side capabilities, and is the underlying logic of order matching in the Reward Tower; the "Wanxiang Zhike" silent analysis adaptive generation system can generate intelligent interactive classrooms without interfering with the teaching scenario; the "Wanxiang Mijing" gamified learning engine supports users to create learned knowledge points into gamified learning content by themselves, realizing co-creation and co-learning across the whole network. The middle layer is the growable Yuanshen avatar AI agent and the 3D immersive "Yuanshen World". Each user has a 7×24-hour online agent that can learn, receive orders and deliver work independently, and supports multi-avatar networking collaboration. The upper layer is the original "Spirit Stone — Spiritual Power — Reputation" three-element economic model and the industry-standardized AI solution package "Tianji Magic Bag", which upgrades the platform from the tool layer to an operating system with currency, capability level and credit system.

The core significance of this architecture lies in: Jianghu Wanxiang does not compete on model parameters, but builds an "application-layer system". General AI tools solve the problem of "single question and answer and generation", AI education and training solve the problem of "exam-oriented learning and courses", while Jianghu Wanxiang solves the complete link of "demand to order, work to payment". The bottom layer reuses the capabilities of existing mature models, and focuses on investing in self-developed engines and closed-loop design. This route not only reduces the capital threshold at the large model layer, but also makes "learn — create — earn" a replicable operational capability.

III. Three revenue curves + full-cycle data assets support a sustainable business model

At present, the AI+ education track is in an outbreak period driven by both policies and the market. According to 2026 data from iResearch, the number of generative AI users has exceeded 600 million, the annual compound growth rate of the GenAI+ education market has reached 37%, and it is expected that the market size will approach 900 billion yuan by 2028. The introduction of AI general courses into primary and secondary schools has spawned a 100-billion-level procurement market, and policies have also shifted from encouraging exploration to mandatory implementation. Jianghu Wanxiang aims at the three major gap pain points in the current industry: the AI literacy enlightenment gap in the K12 stage, the learning-practice disconnection gap in the university stage, and the skill monetization gap in the workplace stage. Through the collaborative coverage of the three versions for full-cycle users, the data assets of the same account system are precipitated across versions, creating two dimensions of time and space for personal capability growth. The user's life cycle value is far higher than that of products in a single track, and the gamified design of xianxia IP also greatly improves user retention and self-propagation efficiency, finally forming a self-driven growth flywheel of "attracting users through learning → generating content through creation → generating transactions through order receiving → feeding back learning with revenue".

In terms of business model, Jianghu Wanxiang has built three mutually reinforcing revenue curves: C-end member subscription + spirit stone recharge, B-end college procurement + enterprise services, and transaction-side task commission + ecological share. The three versions cooperate to form complementarity in customer acquisition and monetization: the youth version has low customer acquisition cost and long user life cycle, the university version realizes batch customer acquisition and builds brand trust, and the general version has high monetization efficiency and higher ARPU value. An information technology teacher from a middle school who participated in the early test feedbacked that "this system solves the problem that schools want to promote AI literacy courses but lack systematic courses and implementation scenarios. Children are willing to learn through gamified level-breaking, and it can also output complete capability reports, helping us fill the gap in policy implementation". A workplace freelance designer who participated in the test said, "In the past, I learned AI by scattered prompts, and I didn't know how to receive orders after learning. Here I can take small orders in the Reward Tower to practice after learning, and the money I earn can in turn improve my skills. The logic is very smooth".

The core team of the company adopts a complementary iron triangle architecture: CEO Wan Qianyi, the founder, has 9 years of experience in AI application and practical operation, is a senior AI architect and full-stack product professional, and is deeply engaged in the integrated development of AI industry and education; COO Xu Meiling, the co-founder, holds a master's degree in educational management from Nanjing Normal University, has more than 10 years of experience in operation and management in the education industry, and is proficient in building the full-link product of "learning, practice, assessment and application"; CMO Cai Lei, the co-founder, is a senior expert in brand marketing and industrial growth, good at brand positioning and channel integration. The three types of capabilities accurately match the needs of the three major user groups of K12, universities and workplace, and provide solid support for full-link closed-loop operation. At present, all core functions of the three versions of the project have been launched. The core milestones include: the full link of Lingya Youth Version, Yuanshenjie University Version and Jianghu Wanxiang General Version has been put into operation, and all landmark functions including more than 180 courses, spiritual root assessment, spiritual card secret realm, Wanxiang Zhike, practical training achievement cockpit, Reward Tower transaction, and Zhanshen Palace OPC incubation have been fully implemented.

Original aspiration of entrepreneurship: Let every AI capability owner be seen, trusted and monetized

Talking about the original aspiration of entrepreneurship, founder Wan Qianyi mentioned a phenomenon that has been repeatedly observed: in the past two years, capital has been concentrated in the large model parameter competition, but the next opportunity of the industry lies in the application layer — in cultivating "AI creators" rather than "AI consumers". Jianghu Wanxiang is not positioned to make a more fancy model, but to let even 9-year-old children change from "scrolling AI content" to "creating with AI". This path not only corresponds to the three major gaps of K12 literacy enlightenment, university learning-practice disconnection, and workplace skill monetization, but also corresponds to the long-term goal of "AI capability owners being seen, matched, trusted and monetized".

As a platform-based enterprise, Jianghu Wanxiang will move forward in two directions in the next step: first, deepen the large-scale path of "benchmark universities + city branches" to form a replicable B-end model; second, enrich the monetization path of "Reward Tower + Yuanshen Avatar", so that the revenue of both C-end and B-end can be precipitated as growing data assets and credit systems. The team judges that the window period for AI talent training and skill monetization has begun, and Jianghu Wanxiang aims to turn this window into a long-term infrastructure, making "learn — create — earn" the default path in the AI era.