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Case StudyEducationResume Screening

From Manual to AI: Resume Screening in Education

Learn how a education company used Arahi AI to automate resume screening, achieving 96% faster faster processing time and 88% savings in operational cost.

Company Profile

Company Type

Private university

Team Size

50-300 staff

Industry

Education

Key Challenge

Struggling with inefficient manual resume screening processes that were slowing growth and increasing operational costs. Their primary concern was enrollment management.

Tools Connected

CanvasBlackboardGoogle ClassroomSlackGmail
Setup Time2 hours
Agents Deployed4 AI agents

The Challenge

This private university had reached a breaking point with their manual resume screening process. With 50-300 staff managing daily education operations, the team was spending an average of 25+ hours per week on repetitive resume screening tasks that added no strategic value. The workload was unsustainable, and errors were becoming more frequent as volume grew.

The consequences extended beyond wasted time. In their education business, delayed resume screening created a cascade of downstream problems — missed deadlines, frustrated stakeholders, and data quality issues that undermined decision-making. The team had tried hiring additional staff, but the cost was prohibitive and training new employees on their complex education processes took months. They needed a solution that could handle their current volume and scale with their growth, without requiring a proportional increase in headcount.

The Solution

The team selected Arahi AI to automate their education resume screening workflow end-to-end. Implementation began with connecting their core tools — Canvas, Slack, and Notion — to the Arahi AI platform. Using the no-code builder, they configured AI agents that replicate their best-performing team member's decision-making process, but at machine speed and consistency.

The AI agents handle every step of the resume screening process: receiving incoming requests or triggers, analyzing the context using education-specific rules, making intelligent routing decisions, executing the core actions, and notifying the right stakeholders. What previously required 45+ minutes of manual work per instance now completes automatically in under 2 minutes. The agents also learn from corrections, continuously improving their accuracy. The team connected Gmail for tracking and reporting, giving leadership real-time visibility into resume screening performance metrics for the first time.

The Results

Measurable improvements across key education resume screening metrics.

Processing Time

96% faster

Before

45+ minutes per task

After

< 2 minutes

Manual Hours per Week

88% reduction

Before

25+ hours

After

< 3 hours

Error Rate

92% fewer errors

Before

8-12% manual errors

After

< 1% with AI

Operational Cost

88% savings

Before

$6,500/month

After

$800/month

Team Capacity

10x scale

Before

Limited by headcount

After

10x throughput

We went from spending half our day on resume screening to having it just happen automatically. The AI agents handle the routine work perfectly, and our education team can focus on the strategic decisions that actually move the needle. I wish we had done this a year ago.

VP of Operations

Private university

Key Takeaways

The most important lessons from this education resume screening automation project.

This education team proved that resume screening automation doesn't require technical expertise — the no-code platform made it accessible to business users.

Scaling resume screening capacity by 10x without adding headcount fundamentally changed the economics of their education operations.

Consistent AI-powered processing eliminated the quality variance that came with different team members handling resume screening differently.

Real-time visibility into resume screening metrics gave leadership the data they needed to make better strategic decisions.

Implementation Timeline

From zero to production in 2 hours — here's how they did it.

Step 1: Connected education tools to Arahi AI

Integrated Canvas, Blackboard, and Google Classroom with Arahi AI using pre-built connectors — no API keys or custom code required. The team verified data flow between systems in under 15 minutes.

Step 2: Configured AI agent business rules

Defined the education-specific rules for resume screening: scoring criteria, routing logic, escalation thresholds, and exception handling. The team used Arahi AI's visual rule builder to translate their existing process into automated workflows.

Step 3: Tested with live education data

Ran the AI agents on a week's worth of historical resume screening data to validate accuracy and identify edge cases. Made minor adjustments to scoring weights and routing rules based on the results.

Step 4: Launched and monitored

Deployed the AI agents to production with the entire team notified via Gmail. Monitored the first 48 hours closely, confirming 99%+ accuracy before reducing oversight to weekly reviews.

Setup Time

2 hours

AI Agents

4 AI agents

Tools Connected

5 integrations

Frequently Asked Questions

Common questions about automating resume screening in education.

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This case study represents a typical customer scenario. Individual results may vary.