Overview
The company’s AI product is Duomian AI Interview. 1. Performance Built independently using McClelland’s iceberg and competency models, Liepin’s years of HR expertise, practical experience and specialist data, plus AI. Emphasizes accurate assessment, ease and efficiency, and value. 2. Applications Serves large companies and SMEs in campus and experienced hiring, assessing university students and white-, grey- and blue-collar workers across recruitment scenarios: 1) Hiring: consistent scientific role criteria and rapid AI screening. 2) Probation: assess whether employees meet permanent-role requirements. 3) Talent reviews: assess development potential to optimize staffing. 4) Transfers and promotions: role-specific models and questions assess fit and identify stronger candidates. 3. Technical innovation 1) Validity and reliability: LLMs and tuned algorithms achieve over 90% scoring consistency with senior interviewers. 2) Broad iceberg-model dimensions: 7 levels and nearly a hundred dimensions match people, roles and organizations. 3) Evidence-Based (EB) technology: claimed industry-first multi-layer probing improves assessment precision. 4) Resume-based personalized questions. 5) Comprehensive intelligent anti-cheating for fairness. 6) Multimodal analysis of voice, semantics and images. 7) Multilingual scoring with fluent Cantonese and English and extensibility to other languages/dialects. 8) Custom rooms, interviewers and questions reinforce employer identity. 4. Core advantages and industry needs 1) Accurate assessment: 1 model, 3 questioning methods, 2 evaluations and 1 anti-cheating approach. A. 1 model: scientific and intelligent modeling. Covers 7 iceberg-model levels and 140+ dimensions, including physical qualities, knowledge/skills, role experience, ability, character, motivation and values. Recruiters enter a role and basic requirements; Doris generates an editable JD, then a competency model based on the confirmed requirements, iceberg theory and industry data, with manual adjustment supported. B. 3 questioning methods: competency questions, proprietary resume-analysis questions and pioneering EB deep probing. Generates editable interview questions from competency models and recruiter needs. Automatically identifies resume strengths and risks for targeted, realistic individual interviews. Patented Evidence-Based multi-stage follow-ups aim to reveal actual capabilities. C. 2 evaluations: anchor-comparison scoring and multimodal assessment. The team argues LLMs cannot directly evaluate candidates reliably. Its proprietary anchor-comparison method combines models and industry expertise, scoring against key dimension anchors for more scientific precision. Voice, meaning, expressions and body movement inform holistic assessment, replicating human interview practice. D. 1 anti-cheating approach throughout. The source reports candidate cheating above 15%, with conventional methods insufficient. LLM-assisted answer analysis identifies cheating using large models, described as an industry first. 2) Efficient and easy to use Create an interview in four steps: a. Confirm role information and resume-question elements. b. Generate the competency model from the role. c. Set interviewer appearance, background, language and opening remarks. d. Configure interview behavior requirements. Customize questions, rooms and interviewers: a. Tailor dimensions, scoring standards and questions to enterprise competency models. b. Match employer branding through rooms, opening statements, automated answers, promotional videos and warm-up questions. c. Customize 2D or 3D digital interviewers to improve candidate engagement and employer presentation. Rich interview reports and filterable report lists help evidence-based screening. Smooth experiences across desktop, mini programs and apps fit different scenarios. Multilingual interviews support local talent needs. Speech recognition and NLP enable natural English, Cantonese and other language/dialect interactions, letting candidates express themselves fully and contributing diverse perspectives to inclusive talent ecosystems. 3) Value: save money, time and effort Money: interview costs are 1/5-1/8 of offline interviews; attendance rises from 60% to 85%. Time: average interview execution cycles fall to 60%~70% of their original duration. Effort: intelligent resume questions identify strengths/risks, patented EB follow-ups probe deeply, anchor-based scoring improves precision and multimodal evaluations combine meaning, voice and expressions. LLM-based anti-cheating addresses impersonation, leaked questions, looking up information and memorized answers, with claimed detection accuracy of 95%.
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我司推出AI 相关产品为多面·AI面试，具体情况如下： 1、 产品性能： 多面·AI面试是依据麦克利兰的冰山模型和胜任力模型理论，结合猎聘在人力资源行业多年的专业知识、实践经验和垂直领域的精准数据沉淀，并采用先进的人工智能技术，经自主研发，打造出具备精准甄别、高效易用、高性价比这三大优势的AI产品。 2、应用领域/典型场景： 多面·AI面试现已为大型企业和中小企业提供服务，广泛应用于校园招聘和社会招聘，面试对象包括高校学生、白领、灰领和蓝领等群体，适用于全场景人才筛选，具体包括： 1）人才招聘：为招聘岗位设定科学统一的评价标准，通过AI面试实现快速筛选； 2）试用期评估：利用AI面试评估试用期员工，判断其能否满足转正要求； 3）人才盘点：在人才盘点中，用AI面试评估被盘点对象的发展潜力，为优化人才结构提供依据； 4）人员调岗/晋升： 根据目标岗位设定匹配的模型和问题，通过AI面试评价候选人和岗位的匹配度，优中选优。 3、 技术创新： 1）信效度高：应用大语言模型，精调算法，与资深面试专家评分一致性大于90%； 2）覆盖冰山模型的丰富维度库：覆盖冰山上下7大层级，近百维度，实现人-岗-组织精准匹配； 3）首创EB技术的多层深度追问：行业首创Evidence-Based技术，多重深度追问，使AI面试结果更加精准； 4）基于简历解析的智能提问：千人千面，让提问更加精准； 5）全方位智能防作弊：为面试公平公正保驾护航； 6）多模态综合分析：语音、语义、图像信息同时采集与分析，确保结果准确性； 7）多语言输入评分：流畅的粤语、英语交互，支持其它语种或方言扩展； 8）个性化定制：支持定制面试间、面试官、面试题等，凸显雇主形象。 4、核心竞争优势（含行业需求理解） 1）优势一：精准甄别（1模3问2评1防）： ①1模：科学建模、智能建模 多面·AI面试覆盖冰山模型7大层级、140+维度，能够全面评估候选人生理素质、知识技能、岗位经验、工作能力、个性品格、动机和价值观。招聘方只需输入岗位名称及人才基本需求，Doris就可以一键生成JD，招聘方也可以进行修改。Doris将根据企业确定的JD和岗位要求，依据冰山理论和多年行业数据沉淀，生成符合该岗位的胜任力评估模型，招聘方可在此基础上进行手动配置和调整。 ②3问：基于胜任力的提问、独有的简历解析提问、首创EB技术的多层深度追问 多面·AI面试可以依据岗位胜任力模型，招聘方亦可根据自身需求，对题目进行智能生成相应面试题目，手动调整。 多面·Al面试可以自动化解析简历中的亮点与风险点，并在面试过程中，针对性地进行提问，使Al面试更逼真地模拟真人面试场景，实现千人于面的效果。 多面·Al面试在行业中首创Evidence-Based技术，在面试过程中，对候选人进行多重深度追问，通过这项荣获国家专利的技术，可以更加精准地评估出候选人的真实能力 ③2评：锚点对比综合评价、多模态综合分析评价 多面团队研究发现，大模型不具备直接评价候选人的能力。对此，多面算法团队基于大模型，结合行业know-how，自主研发了“锚点对比评分法” ，该方法通过锚定维度的关键评分点进行评分，使评估更加科学，结果更加精准。 真人面试场景中，面试官通常会综合候选人的语音、语义、表情及肢体动作等信息，对候选人做出全面的评价。多面·AI面试利用多模态综合分析技术，也可以逼真地还原真人面试的综合评估过程。 ④1防：全程智能防作弊 随着大模型的普及，候选人越来越多地利用大模型来作弊。数据显示，当前候选人作弊率已超15%，传统的防作弊手段已无法全面监测候选人的作弊行为。多面利用大模型对作答结果进行智能辅助分析，可有效识别候选人利用大模型作弊的行为，这项能力为行业首创。 2）优势二：高效易用 ①轻松创建：四步轻松创建AI面试 a.确认面试岗位：填写面试岗位信息，配置简历提问要素 b.搭建面试模型:基于岗位信息生成胜任力模型 c.设置面试信息：自定义面试官形象、背景、语言 及开场词 d.设置面试行为规范 配置面试行为及规范要求 ②个性化定制面试题、面试间、面试官 a.根据本企业岗位胜任力模型定制个性化面试维度、评分标准与面试题：企业可根据本企业岗位胜任力模型，定制企业个性化面试维度、评分标准与专属面试题 b.结合企业雇主品牌形象定制个性化面试间：企业可根据自身雇主品牌形象定制个性化面试间，包括: 自定义开场词设置智能答疑内容、放置企业宣传片、预设热身题等 c.通过“数字分身定制属于自己的数字面试官：企业可根据自身需求，定制2D或3D数字面试官，可增强候选人好感度凸显雇主形象。 ③丰富的智能面试报告 报告列表页支持各种筛选方式，便捷招聘方操作：面试报告中包含丰富的信息，帮助招聘方更加科学有据地筛选人才。 ④三端流畅 PC、小程序、APP三端体验真实流畅，适用于不同场景 ⑤多语言能力：支持多语言面试 招聘方有时非常注重企业的本地化人才储备，更加青睐具备当地方言/语言能力的候选人。得益于先进的语音识别和自然语言处理技术，多面为不同语言背景（例如英语、粤语等）的候选人打造了一个平等的竞技场，流畅、自然的多语种/方言交互体验，让候选人充分表达，进而为组织注入多元化的思维和视角，帮助企业构建一个更包容广阔的人才生态圈。 3）优势三：高性价比：省钱、省时、省心 ①省钱：降本增效: 更低成本，更高到面率 面试成本是线下面试的1/5-1/8；到面率从传统线下面试的60%提升至85% ②省时 更节省面试时间：使用多面·AI面试可以平均缩短面试执行周期至原来的60%~70% ③省心：全程真智能，用着真省心 a.简历解析提问 智能识别简历中的亮点/风险点，面试实现千人干问。 b.智能追问 国家专利，首创EB技术对候选人进行多重深度追问。 c.锚点比对评价 锚定维度的关键评分点进行评分，是评估更加科学，结果更加精准。 d.多模态评价 实时综合分析候选人语义、语音和表情，评估更立体。 e.全程智能防作弊 引入大模型综合防范替考、泄题、查资料和背题等作弊手段，检测准确率达95%。