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Case studiesScoutie
ScoutieHR Tech / Talent Acquisition2025

An AI recruiter that sources, screens and interviews 24/7

Recruiting teams burn roughly 80% of their hours on sourcing and first-round screening — the part of the funnel where speed matters most and where great candidates evaporate fastest. We built a four-part AI recruiter — sourcing, outreach, voice-based screening interviews, and a unified pipeline that hands off cleanly to the customer's ATS.

Time-to-hire
18 days
Offer acceptance
87%
Candidates screened
10×
Sourcing time
↓ ~80%
Scoutie/ Sourcing for · Senior Infra Engineer
ATS · Ashby● Synced 2m ago+ New role

Sourced

412

Outreach

188

AI screened

64

Human interview

18

Offer

6

AI-ranked candidates

AllAI screenedHot leadsSort: match ↓
CandidateMatchComp bandStatus
NK

Naomi Kapoor

Staff Engineer, Infrastructure · Stripe

94

AI match

$185–215K
Voice-screened

87% pass · 7m ago

MO

Marcus Ojo

Senior Engineer, Platform · Cloudflare

91

AI match

$185–215K
🎙Screen scheduled

Tomorrow 14:00

YT

Yuki Tanaka

Senior SRE · GitHub

88

AI match

$185–215K
Outreach sent

Day 2 · no reply yet

PI

Priya Iyer

Staff Backend · DoorDash

86

AI match

$185–215K
Replied · interested

Day 1

JS

Jonah Steiner

Senior Engineer · Datadog

82

AI match

$185–215K
Passed on role

Salary mismatch

LB

Layla Brooks

Senior Backend · Notion

80

AI match

$185–215K
🎙Awaiting screen
+18 candidates sourced overnight from LinkedIn searchReview now →
🎙

AI voice screen

Naomi K. · 18 min call · ended 7 min ago

● Pass · 87% confidence

Skill match

Strong — distributed systems, on-call

Motivation

Late-stage growth, infra ownership

Red flags

None surfaced

Salary fit

$190K asked · within band

Role velocity

↑ ahead of pace

Time-to-hire (proj)

18 days

vs 34 avg

Offer accept (last 5)

87%

industry: 62%

The bottleneck

Hiring scales linearly with headcount in most recruiting orgs — more roles means more recruiters, with all of the coordination cost that implies. The underlying process is the bottleneck, not the team. Top candidates routinely went cold while waiting for a human to read a resume or schedule a first call.

The opportunity was to compress the top of funnel — sourcing and first-round screening — down to something that could run continuously, in parallel, across every open role.

What we built

The system is four connected layers:

1. Sourcing — Chrome extension

Parses a job spec, queries LinkedIn, and surfaces a ranked candidate list with reasoning attached for each match. Recruiters get a shortlist instead of a search.

2. Outreach

Personalized messaging across connection requests, InMails and email. The agent picks the channel, drafts the copy, and follows up on its own schedule.

3. Voice screening

An AI voice interviewer runs first-round screening calls around the clock and returns a structured assessment per candidate — skill match, motivation, red flags, follow-up questions a human should ask. Candidates can schedule inside their own timezone without a recruiter ever picking up the phone.

4. Unified pipeline

ATS sync, real-time analytics, and a single view of every active candidate. A recruiter who used to live in five tools now lives in one.

Outcome

Average time-to-hire of 18 days. Offer acceptance rate of 87%. Recruiters screen roughly 10× more candidates than before, with ~80% less time spent on sourcing. A single recruiter now covers the throughput that previously required a small team.

Why it worked

  • Voice was non-negotiable. Most "AI recruiting" products stop at resume scanning. The actual win is screening — and screening at scale required a real voice agent, not a chatbot.
  • One pipeline, not five tabs. Cutting the recruiter's tool surface was as much of a win as adding AI to it.

"A recruiter that sources 500 candidates, screens 50, and delivers 10 finalists before your team finishes their morning coffee."