A leading agri-food company ran nationwide campus hiring with concurrent roles across product, sales, and engineering.
They faced a sudden surge of applications concentrated in short windows, their teams needed fast, consistent decisions without losing candidate experience or draining HR bandwidth.
In one deployment the client processed 40,000+ resumes and ran 7,000+ interviews using MokaHR’s AI tools, revealing both the scale and the urgency of the problem.
Challenge
Their hiring cycle showed three pain points:
High-volume campus hiring across regions.
Nationwide campus outreach produced sharp surges of resumes within short windows, making manual initial screening difficult to complete in a timely manner.
Parallel hiring across multiple functions.
Multiple roles including product management, sales, and engineering, were interviewed simultaneously across several rounds. Evaluation criteria and feedback channels differed between roles and rounds, resulting in scattered feedback.
HR coordination and review burden. Consolidating multi-round, multi-role feedback required significant alignment and replay, increasing HR’s coordination workload and stretching decision cycles.
Solution
To directly address the challenges, the client deployed MokaHR’s AI-powered ATS to streamline and coordinate their hiring process—turning a large, distributed operation into an automated and highly efficient workflow.
Shift HR to high-value work with AI resume screening. Role-specific screening models automatically rank incoming resumes so recruiters no longer waste time on obvious mismatches, enabling timely shortlists even during short-volume spikes.With administrative triage reduced, recruiters concentrate on interviewing, candidate engagement, and offer negotiation — the work that actually moves candidates through the funnel.
Build up structured, role-aware interview flow. The client leverage AI interview summary to ensure every function and round evaluates the same core competencies, reducing variance in what interviewers record. Live transcription and AI interview summaries centralize impressions and ratings into a single evaluation record, eliminating fragmented feedback channels and simplifying multi-round handoffs.
Results
With MokaHR in production, the client saw measurable improvements: faster shortlisting, consistent evaluation across rounds, and improved interview-to-offer outcomes (the slide shows a ~22% uplift in conversion after structured interviews).
- 40,000+ resumes screened through Smart Resume Screening, allowing recruiters to handle peak campus volumes in hours instead of days.
- 7,000+ interviews supported with AI Interview Summaries, giving hiring managers structured, comparable insights rather than fragmented notes.
- 22% increase in interview-to-offer conversion, reflecting faster feedback cycles and more precise hiring decisions across functions.
Conclusion
By standardizing evaluation with MokaHR’s AI Resume Screening and AI Interview Summary, the client transformed a chaotic campus surge: 40,000+ resumes and 7,000+ interviews, into a predictable, candidate-centered hiring engine that lifted interview-to-offer conversion by 22% and freed HR to focus on strategic talent decisions, turning scale into a sustainable competitive advantage.
