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%
Sourced
412
›Outreach
188
›AI screened
64
›Human interview
18
›Offer
6
AI-ranked candidates
Naomi Kapoor
Staff Engineer, Infrastructure · Stripe
AI match
87% pass · 7m ago
Marcus Ojo
Senior Engineer, Platform · Cloudflare
AI match
Tomorrow 14:00
Yuki Tanaka
Senior SRE · GitHub
AI match
Day 2 · no reply yet
Priya Iyer
Staff Backend · DoorDash
AI match
Day 1
Jonah Steiner
Senior Engineer · Datadog
AI match
Salary mismatch
Layla Brooks
Senior Backend · Notion
AI match
AI voice screen
Naomi K. · 18 min call · ended 7 min ago
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 paceTime-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."
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