MoSeeker AI Interview

What this page covers

• Overview of the MoSeeker AI Interview solution.
• Core capabilities and integration options of MoSeeker AI Interview.
• Quantitative performance metrics and outcomes of the AI interview system.
• Key advantages such as automation, anti-cheating, scalability, and multi-platform support.
• Scoring architecture, GPT assistant, and automatic question generation features.
• End-to-end workflow for recruiters and candidates using AI interviews.
• Customer stories from Danone, Mars, and Shiseido deploying MoSeeker AI Interview.

Table of contents

1. AI Interview hero and overview hero
2. MoSeeker AI Interview product overview and capabilities product_overview
3. Performance metrics and outcomes feature_list
4. Contact Sales call-to-action cta
5. Key Advantages overview feature_list
6. Highly Automated interviews feature_list
7. Advanced Anti-Cheating mechanisms feature_list
8. Scalable Application for large recruitment feature_list
9. Multi-Platform Support for interviews feature_list
10. A True Smart Experience and scoring architecture product_overview
11. Multi-Level Scoring System description definition
12. GPT Assistant (MoGPT) capabilities feature_list
13. Automatic Question Generation feature_list
14. Easy for Recruiters & Simple for Candidates process how_it_works
15. Customer Stories using MoSeeker AI Interview case_study

AI Interview hero and overview

MoSeeker AI Interview is introduced as an online self-service interview solution that automates the full interviewing process to efficiently and fairly assess candidates while integrating with existing recruitment systems.

• Enables organizations to conduct online self-service interviews for candidates.
• Aims to assess candidates’ abilities with fairness and accuracy.
• Designed to integrate with existing ATS and HCM systems.
• Supports both campus recruitment and lengthy social recruitment processes.
• Allows candidates to complete interviews independently once configured by recruiters.

MoSeeker AI Interview product overview and capabilities

The product overview explains MoSeeker AI Interview’s capabilities including online self-service interviews, integration with ATS and HCM solutions, applicability to different recruitment types, and multidimensional AI assessment.

• Provides online self-service interviews that candidates can start anytime, anywhere.
• Can be seamlessly integrated with various ATS and HCM systems.
• Supports campus hiring and longer social recruitment cycles.
• Uses AI algorithms to deliver multidimensional assessments of performance.
• Enables full interview completion after recruiters pre-configure the process.

Performance metrics and outcomes

This section summarizes measured outcomes such as the reported consistency between AI and human evaluations, man-days saved in campus recruitment, and interview throughput within a three-day window.

• AI evaluation results are reported as up to 90% consistent with human evaluations.
• The system can on average save 450 man-days in campus recruitment.
• Capable of completing 10,000 interviews within three days.
• Claims to significantly improve recruitment efficiency and reduce costs.
• Aims to maintain objectivity of evaluation during large-scale hiring.

Contact Sales call-to-action

Visitors are encouraged to contact the MoSeeker AI Interview sales team through a provided form link.

• A Contact Sales form is offered via a Feishu link.
• The call-to-action targets organizations interested in MoSeeker AI Interview.
• The form serves as the primary sales inquiry channel on the page.

Key Advantages overview

The key advantages section introduces MoSeeker AI Interview’s main strengths, emphasizing automation, anti-cheating measures, scalability, and multi-platform support.

• Highlights high automation across the interview lifecycle.
• Presents anti-cheating mechanisms to protect interview integrity.
• Describes scalability for large-scale recruitment scenarios.
• Mentions support for multiple platforms and response formats.

Highly Automated interviews

This section explains how MoSeeker AI Interview automates steps before, during, and after interviews to reduce manual intervention and save HR time.

• HR configures interview questions and the system sends invitations automatically.
• Candidates follow system prompts to complete interviews.
• Candidate performance can be reviewed and referenced for AI evaluation afterward.
• High automation is described as reducing manual intervention.
• The automated flow is positioned as saving time for HR teams.

Advanced Anti-Cheating mechanisms

The anti-cheating section details mechanisms such as randomized questions, monitoring tools, and behavior detection intended to safeguard interview fairness.

• Employs randomized interview questions to limit answer sharing.
• Uses webcam monitoring during interviews.
• Includes screen monitoring capabilities.
• Applies behavior detection to identify suspicious activity.
• Claims these mechanisms significantly reduce cheating incidents.

Scalable Application for large recruitment

This section describes MoSeeker AI Interview’s scalable architecture, emphasizing high concurrency, low latency, fast deployment, and suitability for large, time-sensitive, and distributed recruitment projects.

• Designed to handle high-concurrency interview workloads.
• Engineered for low-latency candidate experiences.
• Can be quickly deployed and launched for projects.
• Supports batch initiation of interviews.
• Suitable for large-scale, time-sensitive, geographically distributed recruitment.

Multi-Platform Support for interviews

The multi-platform section outlines compatibility with various devices and platforms, including WeChat, and support for multiple response formats such as video, audio, and text-based answers.

• Compatible with PCs, smartphones, tablets, and other web-based devices.
• Allows interviews to be conducted via WeChat.
• Supports video response submissions.
• Supports audio responses from candidates.
• Includes multiple choice and open-ended question responses.

A True Smart Experience and scoring architecture

This section introduces a smart, layered scoring architecture that evaluates candidates across multiple capability levels and supports customization for specific industries and clients.

• Scoring model spans basic multimodal capability evaluation.
• Incorporates competency-based evaluation aligned with an iceberg model.
• Includes customizable top-level models for particular industries.
• Allows tailoring for individual clients’ evaluation needs.

Multi-Level Scoring System description

The multi-level scoring system is defined as combining multimodal, competency-based, and domain-specific models to evaluate image, voice, and content while following standardized criteria to help minimize bias.

• Evaluates candidates on image-related appearance signals.
• Assesses voice characteristics of candidate speech.
• Analyzes content of textual or spoken responses.
• Employs basic multimodal, competency, and domain-specific models.
• Standardized criteria are intended to help reduce unconscious bias.

GPT Assistant (MoGPT) capabilities

The GPT Assistant, MoGPT, is described as an integrated large language model component that performs targeted assessments, checks answer relevance, and provides detailed feedback and decision support.

• MoGPT is integrated as part of MoSeeker AI Interview.
• Powered by a large language model.
• Conducts targeted assessments based on predefined scoring points.
• Evaluates relevance of candidates’ answers to questions.
• Generates detailed feedback highlighting strengths and improvement areas.

Automatic Question Generation

Automatic question generation capabilities create personalized, job-description-based interview questions, analyze their tested points, support custom question bank imports, and are positioned as reducing HR workload and inspiring interviewers.

• Generates personalized interview questions per position from the JD.
• Analyzes key points each generated question is intended to test.
• Allows companies to import their own question banks.
• Described as greatly reducing HR burden in question design.
• Generated questions are said to inspire interviewers and improve efficiency.

Easy for Recruiters & Simple for Candidates process

This section outlines an end-to-end workflow where recruiters and candidates complete minimal manual steps while the system automates question setup, invitations, interviews, AI scoring, and report generation.

• Covers preparation activities such as creating questions and setting time.
• Includes invitations and employer branding steps.
• Automates interview execution and AI scoring.
• Generates evaluation reports as part of a closed-loop process.
• HR and interviewers only complete specific highlighted steps in the flow.

Customer Stories using MoSeeker AI Interview

Customer stories showcase how Danone, Mars, and Shiseido use MoSeeker AI Interview to automate interviews, manage high candidate volumes, and support international recruitment, including WeChat-based experiences.

• Danone deployment enables on-demand 24/7 candidate interviews.
• Danone uses in-depth competency assessments and smart scheduling without manual allocation.
• Mars handles tens of thousands of campus candidates with automated workflows.
• Mars case reports streamlined recruitment, shorter cycles, and cost reduction.
• Shiseido deployment automates from invitation to multi-dimensional evaluation via WeChat.

Facts index