As spring arrives, a new wave of recruitment is underway, and job seekers are eager to find their ideal career opportunities. In addition to traditional campus and social recruitment models, an innovative “cloud-based” recruitment concept has quickly emerged, becoming increasingly popular among both companies and job applicants.
“Traditional recruitment methods are often inefficient, especially when it comes to handling the massive volume of resumes submitted via job websites—a process that is time-consuming and labor-intensive. For employers facing thousands of applications, efficient screening has long been a major industry challenge.” Wang Xiangdao, founder of Shanghai MoSeeker Network Technology Co., Ltd., explained that when they started their business in Xuhui, they targeted this very issue. They developed “MoSeeker,” a mobile recruitment system based on WeChat, which uses precise algorithms to match candidates and job openings, and incorporates AI interview technology to enable more accurate and efficient assessments, significantly improving the effectiveness of talent recruitment.
In MoSeeker’s office, an electronic screen displays recruitment data in real time. Hot industries, regional distribution, job types, resume submissions, candidate educational backgrounds—all intuitively reflect current market trends in recruitment. According to statistics, MoSeeker now serves over 1,000 well-known large enterprises, such as Shanghai Disney Resort and Shentong Metro, helping them recruit outstanding talent. Meanwhile, with its user-friendly mini-program platform, MoSeeker has accumulated over ten million job seeker users, forming an extensive talent pool.
Applicants can simply use the MoSeeker account on WeChat to participate in AI-powered video interviews. By recording responses to employer-defined questions and uploading the footage, the MoSeeker system will automatically assess and score their performance. Everything from posture, facial expressions, and eye contact to language proficiency and other subtle details is thoroughly evaluated by MoSeeker’s “eagle-eyed” system.
This AI interview system uses a multidimensional approach to comprehensively evaluate candidates. The first dimension is visual: the system analyzes the video in real time, capturing the candidate’s appearance and demeanor, and monitors whether they maintain consistent eye contact with the camera or display distracted behaviors. The second dimension is auditory: the system evaluates vocal characteristics to recognize whether speech is coherent and clearly articulated. The third dimension is content-based: the system accurately transcribes the audio into text and performs in-depth analysis of the content, such as the correctness of English grammar, habitual verbal expressions, the richness and relevance of responses, and even detects frequently repeated phrases.
Chief Technology Officer Han Zicheng further explained: “The MoSeeker system is equipped with advanced speech-to-text technology and large-scale language models, which can distill lengthy candidate responses into key points, allowing employers to quickly access essential information and significantly easing the burden of reviewing interview videos. Moreover, the system conducts deep analysis of the answers, evaluating relevance to the questions, richness of information, and logical rigor. It then generates a comprehensive and objective AI scoring report, providing valuable insights for companies.“
For example, when recruiting for sales positions, the MoSeeker AI interview system includes specially designed evaluation modules that thoroughly analyze whether candidates demonstrate enthusiasm during communication, their level of extroversion, and overall suitability for sales roles. This results in a highly customized set of assessment criteria. In the future, employers will be able to further tailor and refine models and algorithms to meet their specific recruitment needs—realizing more efficient and accurate processes for screening and evaluating candidates, and selecting top-tier talent.
Reporter: Yang Yixiu, Zhu Liang, Lu Haijie
Editor: Chen Haixiao
Proofreader: Wei Li
Original Report
