Company Profile
Company Type
Mid-size law firm
Team Size
10-50 attorneys
Industry
Legal
Key Challenge
Struggling with inefficient manual ticket routing processes that were slowing growth and increasing operational costs. Their primary concern was contract review accuracy.
Tools Connected
The Challenge
This mid-size law firm had reached a breaking point with their manual ticket routing process. With 10-50 attorneys managing daily legal 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 legal 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 legal 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 legal ticket routing workflow end-to-end. Implementation began with connecting their core tools — Clio, Google Drive, and Gmail — 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 legal-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 legal 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 legal business of our size, that translates directly to the bottom line.”
Operations Director
Mid-size law firm
Key Takeaways
The most important lessons from this legal ticket routing automation project.
This legal team proved that ticket routing automation doesn't require technical expertise — the no-code platform made it accessible to business users.
Scaling ticket routing capacity dramatically without adding headcount fundamentally changed the economics of their legal operations.
Consistent AI-powered processing eliminated the quality variance that came with different team members handling ticket routing differently.
Real-time visibility into ticket routing 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 legal tools to Arahi AI
Integrated Clio, LawPay, and DocuSign 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 legal-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 legal 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
2 hours
AI Agents
4 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating ticket routing in legal.
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