How a Global Staffing Firm Standardized Candidate Screening with lizzyAI

How a Global Staffing Firm Standardized Candidate Screening with lizzyAI

Driving higher data completeness, consistent evaluations, and scalable interviews across a global workforce

Customer Overview

Labor Inbound is a global staffing firm that manages thousands of active candidates and supports large-scale workforce programs. With a proprietary ATS and an existing AI-driven matching system, the team places a strong emphasis on structured candidate data, accuracy, and scalability.

As hiring volumes grew, Labor Inbound needed a way to consistently capture high-quality candidate information—without increasing operational burden or relying on costly external interviewers.

The Situation: Managing High-Volume Candidate Screening at Scale

Labor Inbound manages a large and continuously evolving candidate pool, with new candidates entering each year and existing profiles requiring periodic updates. While resumes and forms provided baseline information, critical data—such as skill depth, eligibility fields, and behavioral indicators—was often incomplete or inconsistent.

The team coordinated with external recruiters to conduct interviews, but this approach created variability in outcomes and limited the firm’s ability to standardize and scale candidate assessment.

The Challenge: Incomplete Data, Inconsistent Interviews, High Cost

Labor Inbound faced several persistent challenges:

• Incomplete candidate profiles
  Key ATS fields were frequently left blank, requiring follow-up and manual effort.
• Inconsistent skill assessment
  Skill levels varied in how they were evaluated and documented, making it difficult to compare candidates reliably.
• Limited personality and fit insights
  Behavioral indicators were largely dependent on recruiter judgment and difficult to scale.
• High reliance on third-party interviewers
  Interviews were costly, inconsistent, and hard to scale efficiently.

Labor Inbound needed a solution that could deliver structured, repeatable, and high-quality candidate data—while fitting seamlessly into existing workflows.

The Solution: Autonomous, Structured Interviews with lizzyAI

Labor Inbound adopted lizzyAI to conduct autonomous, multilingual interviews at scale, replacing most third-party screening interviews and standardizing candidate assessment from the first interaction.

With lizzyAI, the firm was able to:

• Conduct interviews 24/7 without recruiter involvement
• Standardize how skills, experience, and behavioral traits are evaluated
• Capture 1–5 skill ratings with contextual justification
• Collect compliance and eligibility information consistently
• Enrich candidate profiles with structured, ATS-ready outputs

lizzyAI interviews were configured to align directly with Labor Inbound’s existing data schema, enabling manual ingestion during the pilot and a clear path to future API integration.

The Results: Higher Completion, Better Data, Real Business Impact

✔ Higher Candidate Completion Rates

Candidates were more likely to complete lizzyAI interviews compared to previously used questionnaires.

✔ Dramatically Improved Data Completeness

lizzyAI significantly reduced missing ATS fields by capturing structured skills, eligibility details, and personality indicators in a single interaction.

✔ Consistent, Comparable Candidate Profiles

Every candidate is evaluated using the same criteria, making comparisons faster and more reliable.

✔ Reduced Screening Costs

By replacing third-party interviewers, Labor Inbound lowered per-interview costs while increasing output quality.

✔ Positive Internal and Client Feedback

Feedback from Labor Inbound’s clients confirmed that lizzyAI is

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‍“definitely adding a tremendous amount of value.”

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The integration was described by leadership as “a game changer” for the business.

What This Enabled for Labor Inbound

• Scalable interviewing without increasing headcount
• Cleaner, richer candidate data feeding existing AI matching systems
• Faster validation of candidate readiness and fit
• A repeatable screening process aligned with long-term growth

By standardizing interviews and improving data quality at the top of the funnel, Labor Inbound strengthened its entire placement workflow.

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Why This Matters for Global Staffing Firms

For staffing organizations managing large candidate pools, data quality and consistency are the foundation of scale. lizzyAI enables firms to move beyond resumes and questionnaires—delivering structured, comparable insights that improve both operational efficiency and placement outcomes.