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OneAn AI screenwriter writes the plot, an AI director breaks down the shots, an AI marketer monitors ad data, an AI R&D engineer modifies code, and an AI recruiter screens resumes.

WhenAI is no longer just a single tool, but teams of AI agents embedded into business processes, new questions arise:

Which models do they call every day?
Who decides which task should use a powerful model and which task should use a cost-effective model?
How are costs calculated? How is stability ensured? How do enterprises manage?

This is the problem that CloudWalkYunqi Platformaims to solve.

Recently, CloudWalkTechnology's YunqiModelHub unified model service platform was officially launched, providing a unified model service entry for enterprise customers, developers, and AI teams.

It is the "model power supply system" in CloudWalk's silicon-based workforce system."Model Power Supply System".

In CloudWalk's product system, the bottom layer isAI infrastructure, the middle layer is the Xingyun Agent Operating System and Mofang Agent Lab, and the top layer consists of AI teams delivering business results.

AI content production studios, AI e-commerce teams, AI marketing teams, AI functional teams, and AI R&D teams all need to continuously call model capabilities.

In the past, when enterprises integrated models, they often had to select models, connect interfaces, calculate consumption, and adjust performance themselves. The more models, the more complex the integration; the more scenarios, the harder to manage costs.

Yunqi PlatformConverging these capabilities into a unified entry point.

Enterprises canYunqi Platformcall multiple model capabilities and pay based on actual usage, makingthe model consumption during AI team operations clearer, more transparent, and manageable.

For enterprises, the focus is no longer"Which model should I integrate?" but "Can my AI team get up and running faster?"

OneAI short drama teams need to generate topics, scripts, storyboards, and visual styles.
OneAI e-commerce teams need to optimize listings, analyze competitors, adjust ads, and review conversions.
OneAI functional teams need to handle recruitment, resumes, meetings, documents, and processes.
OneAI R&D teams need to understand requirements, generate code, test, review, and deliver.

Behind these tasks, the requirements for model capabilities are completely different.

Some tasks require stronger reasoning, some require faster response, some require lower cost, and some require multimodal capabilities.

Yunqi PlatformIn the next phase, it will further upgrade automatic model orchestration and scheduling capabilities, selecting better combinations among multiple open-source and closed-source models based on task type, quality requirements, response speed, and cost targets.

This meansAI teams can focus on achieving business goals, while underlying model capabilities areYunqi Platformcontinuously supplied and scheduled.

The Xingyun Agent Operating System is responsible for makingAI teams run.
MofangAgent Lab is responsible for building roles, skills, and tools.
Yunqi PlatformIt is responsible for stably supplying model capabilities.

From model services to agent construction, and then toAI team operations, CloudWalk is completing the key infrastructure for enterprises to use silicon-based labor.

In the future, enterprises usingAI teams will increasingly resemble using a new type of productivity infrastructure:

accessible anytime, on-demand, with transparent costs and continuous evolution.

Yunqi PlatformThe launch of is a key step in the implementation of this system.