Chengdu Wuniu Technology (成都午牛科技有限公司)

Solution

Wuniu used Alibaba Cloud Bailian and Qwen-Plus to turn blue-collar recruiting data into a structured AI workflow instead of a manual back-office process. Candidate resumes and employer job postings arrive as natural-language text with missing fields, colloquial phrasing, or policy risks, so the company calls Qwen-Plus through Bailian and uses prompt engineering to force standardized JSON output that downstream systems can parse automatically. On the candidate side, the model extracts identities, contact details, roles, skills, and work history, normalizes loose expressions such as forklift-driving or manual-loading ability, and blocks politically sensitive, sexual, violent, or otherwise illegal content. On the employer side, the same stack splits multi-role postings into standard job cards and flags discrimination, compensation, or compliance problems before publication. The result is a recruiting data loop that is simultaneously structured, safer, and far less labor intensive.

Data flow

Resume text and employer job descriptions are submitted to Bailian, where Qwen-Plus turns free-form language into standardized JSON. Structured outputs feed downstream recruiting workflows, while the same inference pass flags risky content and publishing problems before data is shown to users.