How a Supply chain management firm Automated Ticket Routing with Arahi AI
See how a supply chain management firm automated ticket routing with Arahi AI. Results: Near-instant average routing time, Significant improvement first-contact resolution. Read the full case study.
Company Profile
Company Type
Supply chain management firm
Team Size
50-250 employees
Industry
Logistics
Key Challenge
Struggling with inefficient manual ticket routing processes that were slowing growth and increasing operational costs. Their primary concern was cost optimization.
Tools Connected
The Challenge
This supply chain management firm had reached a breaking point with their manual ticket routing process. With 50-250 employees managing daily logistics operations, the team was spending an average of 25+ hours per week on repetitive ticket routing 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 logistics business, delayed ticket routing 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 logistics 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 logistics ticket routing workflow end-to-end. Implementation began with connecting their core tools — ShipStation, Google Sheets, and Airtable — 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 ticket routing process: receiving incoming requests or triggers, analyzing the context using logistics-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 Slack for tracking and reporting, giving leadership real-time visibility into ticket routing performance metrics for the first time.
The Results
Measurable improvements across key logistics ticket routing metrics.
Average Routing Time
Near-instant
Before
Minutes
After
Seconds
First-Contact Resolution
Significant improvement
Before
Below target
After
Above target
Misrouted Tickets
Major reduction
Before
Common
After
Rare
Customer Satisfaction
Notable increase
Before
Below target
After
Above target
Support Cost per Ticket
Significant savings
Before
High
After
Much lower
“The ROI came quickly. Our ticket routing throughput increased significantly while our error rate dropped dramatically. For a logistics business of our size, that translates directly to the bottom line.”
Operations Director
Supply chain management firm
Key Takeaways
The most important lessons from this logistics ticket routing automation project.
AI-powered ticket routing automation dramatically reduced manual processing time for this logistics team, freeing staff to focus on high-value strategic work.
Implementation took less than a day — the no-code approach meant no IT bottleneck or months-long development cycle.
Error rates dropped significantly, improving data quality and downstream decision-making.
The ROI was realized quickly, with the solution paying for itself through cost savings and productivity gains.
Implementation Timeline
From zero to production in 3 hours — here's how they did it.
Step 1: Connected logistics tools to Arahi AI
Integrated ShipStation, FedEx API, and UPS API 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 logistics-specific rules for ticket routing: 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 logistics data
Ran the AI agents on a week's worth of historical ticket routing 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 Slack. Monitored the first 48 hours closely, confirming high accuracy before reducing oversight to weekly reviews.
Setup Time
3 hours
AI Agents
2 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating ticket routing in logistics.
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This case study represents a typical customer scenario. Individual results may vary.