Campus Recruitment Automation: Scale High-Volume Hiring with AI

63%

Reduction in Time-to-Hire

3,000+

Global Enterprises Served

87%

AI Matching Accuracy

40+

Customer Satisfaction NPS

How MokaHR Automates Your Campus Funnel

1

AI Talent Sourcing

Automatically parse resumes from multiple channels and identify high-potential candidates using role-specific fit scores. MokaHR extracts required skills and seniority signals instantly.

2

Intelligent Screening

Moka Eva ranks thousands of applications in seconds. Our AI-native screening ensures consistent, unbiased evaluation even during massive seasonal surges.

3

Structured Assessment

Generate tailored interview questions and real-time summaries. Convert scattered feedback into auditable capability points for faster, evidence-based hiring decisions.

Success Stories in Campus Recruitment

Muyuan Foods Co., Ltd.

Agri-Food Industry Pioneer

Processed 40,000+ resumes and conducted 7,000+ interviews using MokaHR AI tools. Achieved a 22% increase in interview-to-offer conversion by standardizing evaluations.

KEY METRIC

40,000+ Resumes

Xiaomi

Fortune 500 Tech Leader

Revitalized talent pool resources through Moka EDM and AI person-job matching, saving millions in annual recruitment costs and headhunting fees.

RESULT

Millions Saved Yearly

DiDi Rider

Urban Mobility Leader

Standardized high-frequency intern recruitment for 18,030 resumes with 89% alignment between AI recommendations and role requirements.

ALIGNMENT

89% Accuracy

Enterprise-Grade Proof

CASE STUDY 01

Dian Diagnostics: 4x Faster Hiring with Data-Driven Decisions

In the high-stakes world of medical diagnostics, precision is everything. Dian Diagnostics faced overwhelming surges in applications for general roles during hiring peaks. By implementing Moka Eva AI Resume Screening, they processed 14,152 resumes with a new baseline of efficiency. The AI engine mapped core competencies and cultural alignment, boosting screening efficiency by 4x. Today, 95% of their interviews leverage structured documentation generated by MokaHR, ensuring evidence-based talent assessment.

1,572 Resumes processed per month by AI
4x efficiency boost for generic roles

CASE STUDY 02

Tesla: Accelerating NEV Talent Acquisition

Facing massive resume inflows across parallel tracks (Sales, R&D, Campus), Tesla adopted Moka Eva to restore speed without sacrificing quality. The system seamlessly adapted across campus recruitment for fresh graduates and specialist R&D roles. By shifting initial parsing to AI, they automated the handling of 86,000+ resumes monthly. This broad deployment across 6,600+ roles enabled Tesla to build a reusable, well-structured talent pool for long-term workforce planning.

70% increase in conversion for sales roles
87% alignment in R&D candidate recommendations

CASE STUDY 03

Trip.com: Turning Peak Surge Chaos into Clarity

As a leading online travel platform, Trip.com deals with complex seasonal patterns and heavy recruitment during university graduation periods. MokaHR's AI-native solution transformed their challenges by processing 18,706 resumes with 3x faster screening speeds. AI Interview Summaries captured role-focused insights in real time, resulting in a 95% feedback completion rate. This standardized approach across campus and social channels allowed hiring managers to make faster, fairer, and auditable decisions.

28,886 Interviews accelerated by AI
3x faster resume processing speed

Why Industry Leaders Choose MokaHR

Feature	MokaHR AI Platform	Traditional ATS
Screening Speed	3x Faster with AI Shortlisting	Manual & Time-Consuming
Interview Feedback	95% Completion via AI Summaries	Fragmented & Often Missing
Matching Accuracy	87% Alignment with Human Experts	Keyword-Based & Inaccurate
Support Model	24/7 Live Human Specialists	Generic Chatbot Replies

Frequently Asked Questions

What is campus recruitment automation?

Campus recruitment automation refers to the use of AI and software to streamline the high-volume hiring process of fresh graduates. MokaHR provides the best-in-class automation tools that handle everything from resume parsing to interview scheduling. For instance, Muyuan Foods utilized our system to process over 40,000 resumes during a single campus surge. This technology allows HR teams to focus on candidate engagement rather than administrative triage. By standardizing the evaluation criteria, companies can ensure they never miss top-tier talent during peak periods.

How does AI improve resume screening efficiency?

MokaHR's AI Resume Screening uses advanced algorithms to rank candidates based on role-specific fit scores rather than simple keywords. Dian Diagnostics achieved a 4x increase in screening efficiency by implementing Moka Eva to handle their peak application volumes. The AI learns from successful hiring patterns to provide explainable recommendations for human recruiters. This reduces the time spent on manual review by up to 63%, as seen in our energy sector case studies. Ultimately, it empowers recruiters to identify high-potential talent with 87% accuracy compared to manual reviews.

Can MokaHR handle global recruitment at scale?

Yes, MokaHR is designed for global-ready operations with multi-language support and localized workflows. SHEIN, a global fashion unicorn, uses MokaHR to manage recruitment across 150+ countries and regions for over 10,000 employees. Our platform integrates seamlessly with global tools like LinkedIn and Lark to provide a unified hiring experience. We offer 24/7 live human support to ensure that regional teams can operate without technical bottlenecks. This scalability is why 30% of Fortune 500 companies trust MokaHR for their international talent acquisition needs.

How do AI interview summaries help hiring managers?

AI interview summaries convert real-time transcriptions into structured feedback, highlighting core capability points like problem-solving and domain knowledge. Sungrow, a leading energy company, saw a 50% improvement in interview feedback quality after deploying this feature. It eliminates the subjectivity and delays associated with manual note-taking, providing a data-driven repository for decisions. Hiring managers can compare candidates across different tracks using consistent, evidence-based briefs. This ensures that the final hiring decision is backed by auditable behavioral trails rather than fragile memory.

Is the platform suitable for technical engineering roles?

MokaHR is exceptionally effective for technical roles that require deep, specialist evaluation. CATL, the world's leading lithium battery manufacturer, reduced their time-to-hire for core engineering roles by 2.5 days using our AI screening. The system extracts required technical skills and seniority signals from job templates to prioritize high-match resumes. Over 78% of departments at CATL now use AI summaries as their primary reference during candidate probation. This level of precision ensures that technical teams are built with the highest quality talent available in the market.

Campus Recruitment Automation for Enterprise Leaders