5 Interviews. 3 Minutes.
Zero Back-and-Forth.

A Senior Product Manager role. 5 shortlisted candidates with complex constraints โ€” a Dubai timezone, a single two-hour availability window, a mid-sprint engineer, and a reschedule. Our AI scheduling pipeline handled all of it, automatically, in under four minutes. Here's exactly what it produced.

Role tested: Senior Product Manager โ€” Embedded Finance, London  ยท  February 2026
"This is a live demonstration using our production scheduling pipeline. These are simulated candidates but the AI processing, calendar logic, and email drafting are real."

5

Candidates coordinated

3m 12s

Fully confirmed

21

Emails generated

~60s

Recruiter time needed

Interview scheduling is the invisible time sink

It's not one meeting. It's fifteen small interruptions spread across three days.

Task Per candidate 5 candidates
Check hiring manager calendar 5 min 25 min
Draft and send proposal email 5โ€“7 min 25โ€“35 min
Process reply, re-check calendar 3โ€“5 min 15โ€“25 min
Book invite + send confirmation 3โ€“5 min 15โ€“25 min
Total ~15โ€“20 min 75โ€“110 min
๐Ÿ—“๏ธ

That's nearly two hours โ€” spread across three days of interruptions

Every email reply breaks focus. Every reschedule re-opens the thread. And when a candidate asks to swap slots, you're back to square one โ€” manually checking a calendar you've already checked twice. The cognitive overhead of tracking five concurrent scheduling threads is real, and it compounds when you're managing multiple roles simultaneously.

What our pipeline actually does

From calendar analysis to confirmed interviews โ€” fully automated, with one human approval checkpoint.

1

Candidates marked Ready to Schedule

Pipeline triggered automatically โ€” no manual handoff

2

Hiring manager's calendar read via API

All 23 existing commitments mapped; available windows identified with 15-minute buffers

3

Each candidate's constraints analysed

Timezones, hard windows, employment constraints, and preferences all factored in

4

Constraint solver assigns optimal slots

Non-conflicting schedule produced in milliseconds โ€” hard constraints prioritised first

5

Personalised proposal email drafted for each candidate

Each email references their specific profile, constraints, and context โ€” not a template

6

Single Slack notification sent to consultant

Full schedule overview + draft summaries โ€” one approval checkpoint, then done

7

Replies monitored and processed automatically

Acceptances โ†’ calendar invite + Meet link + confirmation email. Reschedules โ†’ re-analysis + new proposal.

8

Reminders sent automatically

24 hours and 1 hour before each interview โ€” every time, without fail

โšก All 5 interviews fully confirmed in 3 minutes 12 seconds

What the pipeline produced

Metric Result
Candidates coordinated5
Time to all emails sent1 min 19 sec
Time to fully confirmed3 min 12 sec
Scheduling conflicts0
Reschedules handled automatically1 (resolved in 38 min)
Calendar invites created5 (with Google Meet links)
Total emails generated21
Consultant approval checkpoints1
Consultant time required~60 seconds

The Final Confirmed Schedule

Mon 23 Feb 11:00 Tom Calloway Contractor, Revolut
Tue 24 Feb 09:00 Leila Nasser Dubai (GMT+4) โ€” 13:00 her time
Wed 25 Feb 13:30 James Okafor GoCardless โ€” only available window all week
Wed 25 Feb 14:30 Priya Anand Lloyds, employed โ€” afternoon only
Fri 27 Feb 11:00 Rachel Byrne Starling โ€” rescheduled automatically

Zero conflicts. All five candidates slotted into the hiring manager's available windows despite 23 existing calendar commitments, a Thursday Amsterdam flight, a Dubai timezone, and one mid-sprint engineer with a single two-hour window all week.

From 2.5 hours to 60 seconds

Step Manual Process ShortlistOps
Read hiring manager's calendar 5โ€“10 minutes 1.2 seconds
Analyse 5 candidates' constraints 15โ€“20 minutes 0.3 seconds
Find non-conflicting schedule 10โ€“15 minutes 0.3 seconds
Draft 5 personalised emails 25โ€“35 minutes ~8 seconds
Consultant review and approval โ€” 60 seconds
Process replies and confirm bookings 15โ€“25 min (multiple sittings) Automatic
Handle 1 reschedule 10โ€“15 min + extra emails Automatic
Create 5 calendar invites with Meet links 10โ€“15 minutes Automatic
Schedule 10 reminder emails 5โ€“10 min (if remembered) Automatic, always
Double-booking risk High (manual tracking) Zero (agent enforces)
Total recruiter time 110โ€“155 minutes ~60 seconds

Real AI outputs, unedited

Three of the 21 emails the pipeline produced โ€” each personalised to the candidate's specific situation.

Sample 1 โ€” Candidate with a single available window

What makes this personalised: The email acknowledges James's hard constraint directly ("the slot you mentioned as your only available window"), references his employer and current project context (GoCardless sprint), and offers specific insight about the interviewer's style. A template cannot do this.

Sample 2 โ€” Candidate in a different timezone (Dubai, GMT+4)

Sample 3 โ€” Automatic reschedule handling (Rachel Byrne)

What this email does well: It surfaces a genuine piece of context (Marcus is in Amsterdam) rather than hiding it. It offers a clear alternative. The whole reschedule cycle โ€” reply received, calendar re-analysed, new proposal drafted and sent โ€” completed in 38 minutes without a single consultant intervention.

What this means in pounds and hours

For a recruitment agency scheduling 30 interviews per week.

8.5h

saved every week

vs. manual scheduling

32h

saved every month

per consultant

ยฃ13,400

saved annually

at ยฃ35/hr consultant cost

Metric Manual ShortlistOps Saving
Time per interview (full cycle) 15โ€“20 min 1โ€“2 min ~17 min
Interviews per week 30 30 โ€”
Time per week 7.5โ€“10 hrs 30โ€“60 min ~8.5 hrs/week
Time per month 30โ€“40 hrs 2โ€“4 hrs ~32 hrs/month
Cost (at ยฃ35/hr) Manual ShortlistOps
Monthly hours on scheduling 35 hrs 3 hrs
Monthly cost ยฃ1,225 ยฃ105
Monthly saving ยฃ1,120 / month
Annual saving ยฃ13,400 / year

And that's before accounting for the compounding effects.

โ†’Zero double-bookings โ€” the agent enforces conflicts automatically
โ†’Faster scheduling โ€” candidates interviewed days earlier, reducing drop-off
โ†’Reliable reminders โ€” no-show rates drop when reminders always go out
โ†’Holiday cover included โ€” the pipeline runs 24/7 regardless of who's in the office

About This Demonstration

ยท

Role: Realistic Senior Product Manager specification for a fictional London fintech (Kestrel Financial Technologies)

ยท

Candidates: 5 fictional candidates designed to represent genuine scheduling complexity โ€” timezone differences, hard constraints, employed candidates, reschedule scenarios

ยท

Hiring manager's calendar: Realistic busy-week calendar with 23 existing commitments and an Amsterdam trip

ยท

Scheduling logic: Real constraint-satisfaction algorithm โ€” the slot assignments shown are what the system actually computed

ยท

Emails: Generated by Claude (Anthropic's AI), personalised to each candidate's profile โ€” exactly as the production system generates them

The candidates are simulated. The complexity is real. The AI processing is real. The time saving is real.

Run your next batch of interviews through the pipeline

Book a demo and we'll run a live scheduling round with your actual candidates and your hiring manager's real calendar โ€” on the call.

Or email us at anas@shortlistops.co.uk โ€” we'll get back to you within 24 hours.

Call or WhatsApp: +44 7388 281312