Arahi AI Logo
Case StudyReal EstateInvoice Processing

How a Growing real estate brokerage Automated Invoice Processing with Arahi AI

See how a growing real estate brokerage automated invoice processing with Arahi AI. Results: 95% faster invoice processing time, 86% savings processing cost per invoice. Read the full case study.

Company Profile

Company Type

Growing real estate brokerage

Team Size

25-100 agents

Industry

Real Estate

Key Challenge

Struggling with inefficient manual invoice processing processes that were slowing growth and increasing operational costs. Their primary concern was agent productivity.

Tools Connected

MLSZillowFollow Up BossHubSpotDocuSign
Setup Time2 hours
Agents Deployed2 AI agents

The Challenge

This growing real estate brokerage had reached a breaking point with their manual invoice processing process. With 25-100 agents managing daily real estate operations, the team was spending an average of 25+ hours per week on repetitive invoice processing 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 invoice processing 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 invoice processing 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 invoice processing 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 invoice processing performance metrics for the first time.

The Results

Measurable improvements across key real estate invoice processing metrics.

Invoice Processing Time

95% faster

Before

3-5 days

After

< 4 hours

Processing Cost per Invoice

86% savings

Before

$15.40

After

$2.10

Error Rate

95% reduction

Before

3.8%

After

0.2%

Early Payment Discounts Captured

642% increase

Before

12% of eligible

After

89% of eligible

Monthly Invoice Volume

7.5x throughput

Before

200 (max capacity)

After

1,500+ processed

Before Arahi AI, our invoice processing process was the bottleneck that every real estate team complained about. Now it's our competitive advantage. We process faster, more accurately, and at a fraction of the cost. Our competitors are still doing this manually.

Head of Strategy

Growing real estate brokerage

Key Takeaways

The most important lessons from this real estate invoice processing automation project.

AI-powered invoice processing automation eliminated 88% of manual processing time for this real estate 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 by over 90%, significantly improving data quality and downstream decision-making.

The ROI was realized within the first month, with the solution paying for itself multiple times over through cost savings and productivity gains.

Implementation Timeline

From zero to production in 2 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 invoice processing: 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 invoice processing 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

2 hours

AI Agents

2 AI agents

Tools Connected

5 integrations

Frequently Asked Questions

Common questions about automating invoice processing in real estate.

Ready to Automate Invoice Processing in Real Estate?

Get results like these for your business. Set up in 2 hours, no coding required.

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