Case Study: Automation in Hiring, From Manual Sourcing to 4–6x Closures

This was during my stint at Colosseum Consulting.

Candidate sourcing is a time-consuming step in hiring. Identifying relevant profiles, reviewing them manually, and reaching out individually took time and effort.

We were a small team and as hiring demands increased - especially for mid to senior roles -the existing process struggled to keep up. This led to slower turnaround times and missed opportunities.

The right choice of automation and AI tools can increase closure rates by 4-6x

My Task

The goal was to explore the use of AI tools to dramatically improve the speed and efficiency of candidate sourcing - without compromising on quality.

This meant building a system that could:

• Rapidly generate large, relevant candidate pools

• Enable faster and smarter shortlisting

• Reduce manual effort in early-stage screening

• Improve overall closure rate

  
  

What I Did

I designed and implemented an end-to-end sourcing and shortlisting system by combining scraping tools, streamlining the data, tweaking the hiring workflows, and leveraging AI for key steps in the process.

• Data Generation: Used LinkedIn scraping tools to generate large candidate lists (hundreds of profiles) within minutes.

• Data Structuring: Pushed this data into Google Sheets, enabling quick filtering based on basic criteria like experience, role, and keywords.

• AI-Powered Customized Notes: Built a layer where candidate data was sent via API calls to LLMs, which generated tailored notes & summaries aligned with specific role requirements. This transformed raw profiles into decision-ready insights.

• Human-in-the-Loop Shortlisting: Recruiters could now scan high-quality summaries instead of raw profiles, enabling much faster and more accurate shortlisting.

• Contact Enrichment: Leveraged external databases to fetch candidate contact details, including phone numbers.

• Automated Outreach: Set up automated WhatsApp messaging to reach out to shortlisted candidates at scale.

• Recruiter Intervention: Candidates who responded and showed interest entered the manual interaction stage, ensuring human effort was focused where it mattered most.

The Result

The system significantly compressed the sourcing-to-engagement cycle - from days (or weeks) to hours.

• 4–6x increase in closure rates

• Massive reduction in manual sourcing and screening effort

• Faster turnaround times for hiring mandates

• Improved focus of recruiter time on high-intent, relevant candidates

Beyond efficiency gains, this system fundamentally shifted sourcing from a manual, effort-heavy activity to a scalable, system-driven process with intelligent filtering and targeted human intervention.

This project has been my favourite piece of work in the recruitment consulting domain.