Facing the pain points of complex task execution, ONES seeks angel round financing through multi-agent collaboration.

In the past two years, AI has been able to write code, create plans, and generate long reports. However, in real - world work, many complex tasks with multiple steps and dynamically changing goals still remain difficult to be "truly completed". Users often still need to intervene frequently, performing task decomposition, process planning, and decision - making coordination. AI mostly stays at the stage of "assisting thinking" rather than "delivering results".

Based on this real - world pain point, initiated by serial entrepreneur Wang Yuan and with a core team composed of members with experience in product, engineering, and system architecture, the "Yiju (ONES)" project was officially launched in September 2025. The project aims to create a new form of AI application - an execution system that can understand user goals, autonomously decompose tasks, continuously drive multi - agent collaboration, and finally deliver results.

Focus on complex task execution scenarios to solve the industry pain point of "inability to truly complete"

The team observed in practice that most current mainstream AI applications are based on dialogues or fixed processes. When the task structure is stable and the goals are clear, these tools can achieve good results. However, in scenarios involving continuously evolving requirements and multi - professional role collaboration, users still need to undertake a large amount of intermediate coordination work, and the value boundary of AI becomes quickly apparent.

This phenomenon is particularly evident in scenarios such as product R & D, system building, and cross - departmental project promotion. Despite the increasing number of relevant tools, whether "things are truly completed" still highly depends on continuous human intervention. This model offsets the efficiency improvement brought by AI to a certain extent and has become a common pain point for enterprises and individual users.

"Yiju (ONES)" chooses to start from this execution gap, attempting to extend the capabilities of AI from "phased assistance" to "full - process execution", enabling the system to work continuously around user goals until results are delivered.

A goal - oriented multi - agent collaboration system to drive continuous task execution

In terms of product form, "Yiju (ONES)" is not a traditional Q&A tool or an automated process platform, but a goal - oriented multi - agent collaborative execution system. Users only need to describe the final goal, and the system will decompose tasks, plan execution paths around this goal, and schedule multiple agents with different capabilities to collaborate in parallel.

Different from fixed - process tools, the execution path of this system is not fully pre - set. Instead, it will be dynamically adjusted according to task progress and external changes. This mechanism enables the system to continuously correct the execution strategy when tasks change, preventing tasks from stagnating or failing midway.

From a technical perspective, the core capabilities of this system lie in the continuous understanding of user intentions and the dynamic management ability of the complex task execution process. This ability does not rely on the performance of a single model but is achieved through system - level collaboration and scheduling to continuously promote complex tasks.

The MVP has been verified, and execution experience is being transformed into platform capabilities

During the project promotion process, the "Yiju (ONES)" team has always focused on validating the core capabilities of the product. Currently, the project has completed the development of the Minimum Viable Product (MVP).

In real - world scenarios such as the construction of complex application systems, the system has achieved a complete closed - loop from requirement input to result delivery, with a matching degree between the delivered results and the expected goals exceeding 90%. This phased achievement verifies the feasibility of the multi - agent collaboration mechanism in complex task execution and provides a foundation of execution data and experience for subsequent product optimization.

The team believes that as the system accumulates more execution experience, relevant capabilities are expected to gradually be transformed into reusable platform capabilities, thus supporting a wider range of application scenarios.

Business model and financing plan

In terms of business model, "Yiju (ONES)" plans to adopt a combination of multiple charging methods mainly based on the subscription system. It will provide basic version services for individual users and small teams, and offer team - edition and enterprise - edition solutions with higher collaboration, management, and customization capabilities for enterprise users. At the same time, the team is also exploring a solution - based charging model for specific business scenarios.

After completing the MVP verification, the project plans to launch the first - round financing, with a proposed financing scale of RMB 4 million. The funds from this round will be mainly used to improve the system - level capabilities of the product, expand the core team, conduct early - stage market verification and user expansion, so as to accelerate the transition from the product verification stage to the large - scale application stage.

From a long - term perspective, the team hopes to continuously optimize the system's capabilities in autonomous decision - making and collaboration efficiency, gradually expand into more high - value industry scenarios, and ultimately form a general intelligent task execution platform.