Company Profile
Company Type
Multi-office realty firm
Team Size
10-50 agents
Industry
Real Estate
Key Challenge
Struggling with inefficient manual ticket routing processes that were slowing growth and increasing operational costs. Their primary concern was deal pipeline velocity.
Tools Connected
The Challenge
This multi-office realty firm had reached a breaking point with their manual ticket routing process. With 10-50 agents managing daily real estate 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 real estate 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 real estate 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 real estate ticket routing workflow end-to-end. Implementation began with connecting their core tools — MLS, HubSpot, 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 real estate-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 DocuSign for tracking and reporting, giving leadership real-time visibility into ticket routing performance metrics for the first time.
The Results
Measurable improvements across key real estate ticket routing metrics.
Average Routing Time
99.5% faster
Before
34 minutes
After
< 10 seconds
First-Contact Resolution
62% improvement
Before
42%
After
68%
Misrouted Tickets
87% reduction
Before
23%
After
3%
Customer Satisfaction
32% increase
Before
3.4/5
After
4.5/5
Support Cost per Ticket
59% savings
Before
$22
After
$9
“The difference is night and day. Our real estate clients used to wait days for ticket routing to be completed. Now it happens in minutes, and the quality is consistently higher than what we achieved manually. Customer satisfaction scores went through the roof.”
VP of Customer Success
Multi-office realty firm
Key Takeaways
The most important lessons from this real estate ticket routing automation project.
This real estate 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 by 10x without adding headcount fundamentally changed the economics of their real estate 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 3 hours — here's how they did it.
Step 1: Connected real estate tools to Arahi AI
Integrated MLS, Zillow, and Follow Up Boss 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 real estate-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 real estate 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 DocuSign. Monitored the first 48 hours closely, confirming 99%+ accuracy before reducing oversight to weekly reviews.
Setup Time
3 hours
AI Agents
4 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating ticket routing in real estate.
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This case study represents a typical customer scenario. Individual results may vary.