HR & Recruitment

Booth and Partners: How we Delivered consistency, speed, and scale in candidate shortlisting

Impact Summary

Reduced execution time per task from ~6–7 minutes → ~1.5–2 minutes (70% faster).
Established standardized screening via auto-generated evaluation rules for every new job description.
Introduced JD-missing detection and notification, ensuring no dead-end screenings and creating a foundation for end-to-end JD lifecycle automation.
Scaled to 9,500+ screenings since June, with 97.8% overall completion rate.
Delivered consistency, speed, and scale in candidate shortlisting, reducing manual recruiter workload.

Overview

Problem

Recruitment teams at Booth & Partners were spending significant time manually screening candidates against job descriptions. With over 250 job descriptions and continuous inflow of resumes, this process often led to:

Inconsistent shortlisting criteria across recruiters (different recruiters applied different interpretations of must-have vs. nice-to-have).
Delayed candidate feedback loops.
Limited visibility into process performance (time per task, rejection/acceptance patterns).
High operational costs tied to repetitive, rules-based evaluations.

Solution

To streamline and scale the screening process, CV Screening Agent was deployed. The workflow integrates:

Airtable as the single source of truth for job descriptions and evaluation rules.
Auto-generation of evaluation rules when a new job description is added to the dashboard. These rules form the standardised basis of candidate screening, ensuring consistency across all recruiters and job roles.
Automated Candidate Scoring & Selection, matching resumes against must-have and nice-to-have criteria.
Zoho Recruit for structured data posting and record management.
Google Chat notifications for real-time recruiter updates.
New conditional branch: if a job description does not exist in Airtable, recruiters are automatically notified to create an entry. This ensures that all future screenings are traceable to a structured JD, preventing process gaps and opening an expansion opportunity for full JD lifecycle automation.
Monitoring Dashboards to track completions, failures, and runtime efficiency

Impact Summary

Reduced execution time per task from ~6–7 minutes → ~1.5–2 minutes (70% faster).
Established standardized screening via auto-generated evaluation rules for every new job description.
Introduced JD-missing detection and notification, ensuring no dead-end screenings and creating a foundation for end-to-end JD lifecycle automation.
Scaled to 9,500+ screenings since June, with 97.8% overall completion rate.
Delivered consistency, speed, and scale in candidate shortlisting, reducing manual recruiter workload.

Overview

Problem

Inconsistent shortlisting criteria across recruiters (different recruiters applied different interpretations of must-have vs. nice-to-have).
Delayed candidate feedback loops.
Limited visibility into process performance (time per task, rejection/acceptance patterns).
High operational costs tied to repetitive, rules-based evaluations.

Solution

To streamline and scale the screening process, CV Screening Agent was deployed. The workflow integrates:

Airtable as the single source of truth for job descriptions and evaluation rules.
Auto-generation of evaluation rules when a new job description is added to the dashboard. These rules form the standardised basis of candidate screening, ensuring consistency across all recruiters and job roles.
Automated Candidate Scoring & Selection, matching resumes against must-have and nice-to-have criteria.
Zoho Recruit for structured data posting and record management.
Google Chat notifications for real-time recruiter updates.
New conditional branch: if a job description does not exist in Airtable, recruiters are automatically notified to create an entry. This ensures that all future screenings are traceable to a structured JD, preventing process gaps and opening an expansion opportunity for full JD lifecycle automation.
Monitoring Dashboards to track completions, failures, and runtime efficiency

Impact Summary

Reduced execution time per task from ~6–7 minutes → ~1.5–2 minutes (70% faster).
Established standardized screening via auto-generated evaluation rules for every new job description.
Introduced JD-missing detection and notification, ensuring no dead-end screenings and creating a foundation for end-to-end JD lifecycle automation.
Scaled to 9,500+ screenings since June, with 97.8% overall completion rate.
Delivered consistency, speed, and scale in candidate shortlisting, reducing manual recruiter workload.

Overview

Problem

Inconsistent shortlisting criteria across recruiters (different recruiters applied different interpretations of must-have vs. nice-to-have).
Delayed candidate feedback loops.
Limited visibility into process performance (time per task, rejection/acceptance patterns).
High operational costs tied to repetitive, rules-based evaluations.

Solution

To streamline and scale the screening process, CV Screening Agent was deployed. The workflow integrates:

Airtable as the single source of truth for job descriptions and evaluation rules.
Auto-generation of evaluation rules when a new job description is added to the dashboard. These rules form the standardised basis of candidate screening, ensuring consistency across all recruiters and job roles.
Automated Candidate Scoring & Selection, matching resumes against must-have and nice-to-have criteria.
Zoho Recruit for structured data posting and record management.
Google Chat notifications for real-time recruiter updates.
New conditional branch: if a job description does not exist in Airtable, recruiters are automatically notified to create an entry. This ensures that all future screenings are traceable to a structured JD, preventing process gaps and opening an expansion opportunity for full JD lifecycle automation.
Monitoring Dashboards to track completions, failures, and runtime efficiency

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HR & Recruitment