EdTech: Tutor Hiring Cycle Slashed from Weeks to Days with AI

Manually sorting through 500+ tutor applications weekly led to hiring delays and candidate drop-offs.

High-potential candidates were often overlooked due to rushed or incomplete manual shortlisting.

Scheduling interviews with multiple candidates and panelists consumed valuable HR time, delaying critical hires.

Recruiters lacked real-time visibility into candidate progress, causing pipeline gaps and stalled decisions.

Interviewers and recruiters had inconsistent evaluations, causing back-and-forth debates and slower approvals.

Delayed offers often resulted in losing qualified candidates to faster-moving competitors in the EdTech hiring race.

LeoBrain’s AI recruiting tool parsed the resumes instantly, shortlisting the top 20% most relevant tutor profiles based on required skills.

AI auto-assessed the quiz round as per the requirements, subject expertise, and student success metrics.

Automated calendar syncing eliminated scheduling backlogs, reducing interview booking time by 70%.

Real-time analytics provided a clear view of each candidate’s pipeline status, accelerating decision-making.

Centralized feedback allowed interviewers and recruiters to score, rank, and finalize candidates on a unified dashboard.

Reduced administrative delays helped the team extend offers within 48 hours, improving acceptance rates significantly.