Overview

A 20-year-old firm sitting on7.5 lakh untapped candidates

This technical staffing firm has been placing contract engineers — piping engineers, field technicians, and specialist operators — into shutdowns, refineries, and multi-year EPC projects for over two decades. Their contracts typically run 6 months to 2 years, which means their placed talent is perpetually cycling back into the job market.

Over the years, they’d accumulated over 7.5 lakh candidate profiles across CVs, Excel sheets, and individual recruiter systems, but had no unified way to search, track, or re-engage this database. The goldmine was there. The tools to mine it weren’t.

Core Problem

100 recruiters. 7.5 lakh profiles. Zero centralised system. Data locked in individual laptops, siloed by recruiter, with no reuse, no search, and no re-engagement capability.

Challenges

1. Data trapped in silos — no central CRM

   With 80–100 recruiters each maintaining their own local databases, there was no shared system to search candidates, track outreach history, or measure source effectiveness. When a recruiter left, so did their data — permanently.

   
   

2. 7.5 lakh untapped candidate profiles

   Every contract engineer placed would return to the job market within 6–24 months. Yet there was no system to track contract end dates, proactively re-engage these candidates, or cross-fit them across 100+ active client requirements.

   
   

3. High job board spend — low internal sourcing

   The firm was spending heavily on Naukri, Indeed, Monster, and LinkedIn job plans — shared logins, downloaded CVs, stored locally. The answer was sitting in their own database, but they had no way to use it.

   
   

4. Low WhatsApp engagement — no feedback capture

   Early outreach via WhatsApp produced just 7–15% engagement, with no way to understand why candidates weren’t responding. Were salaries off? Wrong domain? Wrong location? The one-way flow gave no answers.

   
   

Solutions

1. Centralised talent database — searchable, reusable

   All 7.5 lakh profiles — previously locked in CVs, Excel sheets, and local recruiter folders — brought into a single searchable system. Recruiters can now search by role, domain, experience, and location across the entire historical pool.

   
   

2. WhatsApp check-interest on historical database

   Automated WhatsApp outreach deployed on the historical database — checking availability and interest for active requirements. Candidates re-engaged at scale without any manual recruiter effort per profile.

   
   

3. Multi-channel real-time sourcing pipeline

   Career page, LinkedIn, WhatsApp, and referrals all connected to Hunar — funnelling active, real-time applicants directly into the pipeline alongside historical data. One view, all sources.

   
   

4. Conversational AI HR outreach using Voice calls

   When WhatsApp engagement plateaued, Hunar Voice AI HRs were deployed for the same outreach. The conversational AI captured not just interest levels but also the reasons behind non-interest — salary expectations, preferred domains, availability — giving recruiters actionable intelligence, not just a connect rate.

   
   

5. Cross-fitting candidates across 100+ clients

   Once a candidate expresses interest, Hunar’s pipeline enables recruiters to cross-fit that profile against active requirements across all 100+ clients and geographies — significantly increasing placement velocity and reducing time-to-deploy for each candidate.

   
   

WhatsApp-only outreach produced 7–15% engagement — constrained by ageing data, WhatsApp policy restrictions on marketing templates, and the inability to capture candidate responses beyond a pre-defined flow. Adding Voice AI to the same outreach lifted engagement to 30% — a 3x improvement — while also surfacing qualitative insights: salary expectations, domain preferences, and availability signals that WhatsApp simply couldn’t capture.