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Case StudyLegalFollow-Up

From Manual to AI: Follow-Up in Legal

Learn how a legal company used Arahi AI to automate follow-up, achieving 96% faster faster processing time and 88% savings in operational cost.

Company Profile

Company Type

Corporate law firm

Team Size

10-50 attorneys

Industry

Legal

Key Challenge

Struggling with inefficient manual follow-up processes that were slowing growth and increasing operational costs. Their primary concern was contract review accuracy.

Tools Connected

ClioLawPayDocuSignGoogle DriveSlack
Setup Time3 hours
Agents Deployed4 AI agents

The Challenge

This corporate law firm had reached a breaking point with their manual follow-up process. With 10-50 attorneys managing daily legal operations, the team was spending an average of 25+ hours per week on repetitive follow-up 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 follow-up 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 follow-up 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 follow-up 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 follow-up performance metrics for the first time.

The Results

Measurable improvements across key legal follow-up metrics.

Processing Time

96% faster

Before

45+ minutes per task

After

< 2 minutes

Manual Hours per Week

88% reduction

Before

25+ hours

After

< 3 hours

Error Rate

92% fewer errors

Before

8-12% manual errors

After

< 1% with AI

Operational Cost

88% savings

Before

$6,500/month

After

$800/month

Team Capacity

10x scale

Before

Limited by headcount

After

10x throughput

What impressed me most was the setup speed. I expected a months-long implementation, but we had AI agents handling our legal follow-up workflow within a single afternoon. The no-code approach meant our team could configure everything themselves without waiting on IT.

Director of Business Operations

Corporate law firm

Key Takeaways

The most important lessons from this legal follow-up automation project.

This legal team proved that follow-up automation doesn't require technical expertise — the no-code platform made it accessible to business users.

Scaling follow-up capacity by 10x 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 follow-up differently.

Real-time visibility into follow-up 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 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 follow-up: 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 follow-up 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 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 follow-up in legal.

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