Company Profile
Company Type
Regional freight company
Team Size
20-100 employees
Industry
Logistics
Key Challenge
Struggling with inefficient manual resume screening processes that were slowing growth and increasing operational costs. Their primary concern was delivery time accuracy.
Tools Connected
The Challenge
Manual resume screening was the biggest bottleneck in this regional freight company's operations. Their team of 20-100 employees processed hundreds of resume screening requests weekly, each requiring multiple steps, cross-referencing against logistics-specific requirements, and coordination between departments. The average resume screening request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.
Beyond the time drain, the quality of their resume screening output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in logistics. A recent audit revealed that 12% of completed resume screening records contained errors that required rework — costing the organization an additional $50K annually in correction and remediation efforts. The leadership team recognized that continuing to throw people at the problem wasn't viable and began searching for an AI-powered solution.
The Solution
Arahi AI provided the automation backbone this logistics team needed. They deployed a multi-agent workflow that breaks the resume screening process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from ShipStation and Google Sheets. The second agent analyzes and processes incoming requests using logistics-specific business logic. The third agent executes actions across connected tools and notifies team members via Airtable.
The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full resume screening workflow was operational within a single afternoon. They used Arahi AI's template for logistics resume screening as a starting point, customized the business rules to match their specific process, and connected their existing tool stack without writing a single line of code. Within the first week, the agents had processed over 200 resume screening instances with 99%+ accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key logistics resume screening metrics.
Task Completion Time
97% faster
Before
2-3 hours average
After
< 5 minutes
Team Productivity
250% increase
Before
Baseline
After
3.5x output
Quality Score
26% improvement
Before
78% accuracy
After
98.5% accuracy
Monthly Cost
85% savings
Before
$8,200/month
After
$1,200/month
Customer Satisfaction
35% increase
Before
3.4/5
After
4.6/5
“What impressed me most was the setup speed. I expected a months-long implementation, but we had AI agents handling our logistics resume screening workflow within a single afternoon. The no-code approach meant our team could configure everything themselves without waiting on IT.”
Director of Business Operations
Regional freight company
Key Takeaways
The most important lessons from this logistics resume screening automation project.
Automating resume screening in logistics delivered immediate, measurable results: faster processing, higher accuracy, and lower costs.
The key to success was connecting existing logistics tools to AI agents rather than replacing the entire tech stack.
24/7 automated processing eliminated backlogs and ensured consistent service quality regardless of volume fluctuations.
Starting with a pre-built template and customizing for logistics-specific requirements dramatically reduced time-to-value.
Implementation Timeline
From zero to production in 90 minutes — here's how they did it.
Step 1: Mapped the existing resume screening workflow
Documented every step of the current manual resume screening process, including decision points, exceptions, and handoffs between team members. Identified which steps could be fully automated versus those needing human oversight.
Step 2: Built the automation in Arahi AI
Used Arahi AI's no-code builder to create the resume screening workflow: connected ShipStation and UPS API as data sources, configured AI decision logic for logistics-specific requirements, and set up automated actions and notifications.
Step 3: Parallel run with manual process
Ran the AI agents alongside the manual process for one week to compare outputs. The AI matched or exceeded human accuracy on 98% of resume screening instances, with the 2% of edge cases automatically flagged for human review.
Setup Time
90 minutes
AI Agents
3 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating resume screening in logistics.
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