On 31st October, at exactly 11:30 AM, the energy inside the training hall felt unmistakably different. This wasn’t just another briefing session. This was preparation for a high-pressure, high-volume Hire-a-Thon, an experiment to test what happens when you combine disciplined recruiter operations with the speed of conversational Voice AI.

Training Day: Setting the Ground for Precision

A total of 40 recruiters (37.5% of freshers, 62.5% of experienced professionals) reported for the final orientation.
They were split into six randomly formed teams:

• Team A (9) – led by Renu (Companies 1, 2, 3)

• Team B (8) – led by Zoya (Companies 4, 5, 6, 7)

• Team C (8) – led by Aman (Companies 8,9,10,12)

• Team D (5) – led by Manish (Company 13)

• Team E (8) – led by Shriya (Companies 14,15,16,17)

• Team F (4) – led by Kalpana (Company 18)

For 45 minutes, all six teams trained simultaneously under Kalpana’s guidance. The session was crisp, structured and deeply operational:

• Logging in and getting comfortable with the system

• Complete dashboard walkthrough

• Understanding recruitment-dashboard terminology

• How call statuses work

• How to create a structurally correct job query

• And most importantly: how to trigger qualification calls

1st November, 9:50 AM, The Hire-a-Thon Begins

All 40 recruiters reported to Harjoth (Manager – Hunar Select).
Team leaders quickly assigned roles. Each recruiter received 1 role (with 1–2 hiring locations).
A job query in our system is simply a more intelligent version of a JD, structured so that our AI can extract information and begin automated qualification.

At 10:00 AM, we started the stopwatch.

Task 1: Sourcing | 10:00 – 10:30 AM

Each recruiter sourced ~300 candidates for their assigned role using filters and exports.
In 30 minutes, the candidate pool reached nearly 12,000 candidates.

Task 2: Job Query Creation | 10:30 – 10:55 AM

Recruiters applied their training to create job queries for their assigned locations.

• Total job queries created: 64

• Completed by 10:55 AM sharp

Then, the moment everyone waited for:

At 10:55 AM, every recruiter hit Check Interest.

Within seconds, WhatsApp messages were triggered across all 12,000 candidates, except 685 numbers that failed due to invalid or inactive WhatsApp accounts.

And this single click set off an entire chain of automated intelligence.

Task 3: The AI Pipeline in Action

1. WhatsApp Interest Flow

Candidates could respond with:

• Yes → Leads to qualification

• No → Loop ends (695 candidates)

• No response → AI calls trigger automatically

198 candidates fully completed the WhatsApp qualification flow.

2. Voice AI Qualification Calls

Five minutes later, our Voice AI agent began calling:

• Anyone who said “yes” but didn’t complete the flow

• Anyone who didn’t respond

• Anyone who partially completed the flow (our Voice AI agent only asked pending questions)

Result of First Calling Cycle

• 4,250 calls picked up by candidates

• 3,223 total AI call minutes processed

• Achieved in: 70 minutes

To put this in perspective:

It would take 40 recruiters, 11 days to do what Voice AI did in 70 minutes.

This is efficiency in raw, operational reality.

Task 4: Qualification, Refreshing in Real-Time

As WhatsApp replies and AI calls continued, the Qualification tab kept refreshing live on the dashboard.
Recruiters monitored candidates who cleared the AI filters, and began making manual calls for deeper assessments:

• Expected CTC

• Career gaps

• Location feasibility

• Role nuance and employer-specific expectations

This layered process, AI qualification + recruiter judgement is what makes the model scalable and reliable.

Out of:

4,250 (AI calls) + 198 (WhatsApp) = 4,448 candidates entered the qualification funnel

Candidates who cleared qualification: 1,209

By 12:05 PM, recruiters had manually spoken to 92 candidates.

Average time taken for candidates to pick recruiter calls after 12:05 PM: ~5 hours

Out of 1,209 qualified candidates:

• 744 were successfully connected with recruiters

• 311 were lined up for interviews

• 31 candidates joined

A single day.
From sourcing → qualification → recruiter evaluation → lineups → conversions.

Conclusion

This Hire-a-Thon wasn’t just a recruitment sprint.
It was a demonstration of how technology can reshape operational realities:

• Weeks of manual calling → compressed into 70 minutes

• Unstructured JDs → converted into extractable job queries

• Unpredictable workflows → transformed into measurable funnels

• Recruiters → elevated to evaluators, not dialers

40 recruiters.
12,000 candidates.
A fully integrated Voice AI + WhatsApp engine.