Company Profile
Company Type
Boutique legal practice
Team Size
20-80 staff
Industry
Legal
Key Challenge
Struggling with inefficient manual appointment scheduling processes that were slowing growth and increasing operational costs. Their primary concern was client intake efficiency.
Tools Connected
The Challenge
Manual appointment scheduling was the biggest bottleneck in this boutique legal practice's operations. Their team of 20-80 staff processed hundreds of appointment scheduling requests weekly, each requiring multiple steps, cross-referencing against legal-specific requirements, and coordination between departments. The average appointment scheduling request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.
Beyond the time drain, the quality of their appointment scheduling output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in legal. A recent audit revealed that 12% of completed appointment scheduling 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 legal team needed. They deployed a multi-agent workflow that breaks the appointment scheduling process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from Clio and Google Drive. The second agent analyzes and processes incoming requests using legal-specific business logic. The third agent executes actions across connected tools and notifies team members via Gmail.
The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full appointment scheduling workflow was operational within a single afternoon. They used Arahi AI's template for legal appointment scheduling 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 appointment scheduling instances with 99%+ accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key legal appointment scheduling 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
“Before Arahi AI, our appointment scheduling process was the bottleneck that every legal 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
Boutique legal practice
Key Takeaways
The most important lessons from this legal appointment scheduling automation project.
AI-powered appointment scheduling automation eliminated 88% of manual processing time for this legal 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 90 minutes — here's how they did it.
Step 1: Mapped the existing appointment scheduling workflow
Documented every step of the current manual appointment scheduling 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 appointment scheduling workflow: connected Clio and DocuSign as data sources, configured AI decision logic for legal-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 appointment scheduling instances, with the 2% of edge cases automatically flagged for human review.
Setup Time
90 minutes
AI Agents
2 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating appointment scheduling in legal.
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