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Case StudyLegalResume Screening

Legal Resume Screening Automation Case Study

This legal case study shows how AI-powered resume screening automation delivered 97% faster improvement in task completion time and 26% improvement in quality score.

Company Profile

Company Type

Legal services company

Team Size

15-60 employees

Industry

Legal

Key Challenge

Struggling with inefficient manual resume screening processes that were slowing growth and increasing operational costs. Their primary concern was billable hour recovery.

Tools Connected

ClioLawPayDocuSignGoogle DriveSlack
Setup TimeHalf a day
Agents Deployed3 AI agents

The Challenge

Manual resume screening was the biggest bottleneck in this legal services company's operations. Their team of 15-60 employees processed hundreds of resume screening requests weekly, each requiring multiple steps, cross-referencing against legal-specific requirements, and coordination between departments. The average resume screening request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.

Beyond the time drain, the quality of their resume screening 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 resume screening 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 resume screening 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 resume screening workflow was operational within a single afternoon. They used Arahi AI's template for legal resume screening 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 resume screening instances with 99%+ accuracy — more than the team typically handled in a month.

The Results

Measurable improvements across key legal resume screening 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

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

Director of Business Operations

Legal services company

Key Takeaways

The most important lessons from this legal resume screening automation project.

Automating resume screening in legal delivered immediate, measurable results: faster processing, higher accuracy, and lower costs.

The key to success was connecting existing legal tools to AI agents rather than replacing the entire tech stack.

24/7 automated processing eliminated backlogs and ensured consistent service quality regardless of volume fluctuations.

Starting with a pre-built template and customizing for legal-specific requirements dramatically reduced time-to-value.

Implementation Timeline

From zero to production in Half a day — here's how they did it.

Step 1: Mapped the existing resume screening workflow

Documented every step of the current manual resume screening 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 resume screening 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 resume screening instances, with the 2% of edge cases automatically flagged for human review.

Setup Time

Half a day

AI Agents

3 AI agents

Tools Connected

5 integrations

Frequently Asked Questions

Common questions about automating resume screening in legal.

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