Portfolio companies almost always have a hiring backlog. The obvious answer — hire more recruiters — is slow and expensive. AI cuts time-to-hire by 50–70% and cost-per-hire by 30–40% by automating sourcing, screening, scheduling, and candidate communications. Growth plans get unblocked. Vacancy cost drops. The recruiter team stays the same size and does 3x the work.
A revenue role sitting open for 42 days at a $150K target salary costs roughly $52K in vacancy cost alone before the paycheck starts. Growth-stage portfolio companies typically carry 8–20 open roles at any time. Meanwhile recruiters are stuck in the manual parts of the funnel — LinkedIn searches, calendar coordination, screening emails.
We deploy inside the existing ATS — Greenhouse, Lever, Ashby, Workable, or the portfolio company's SMB stack — plus LinkedIn Recruiter, email, and calendaring. No new recruiter tool. AI shortens the mechanical steps; humans keep judgment.
Time-to-hire drops from 42 to 14–20 days. Cost-per-hire down 30–40%. The recruiter team runs 3–5x the throughput. Vacancy cost captured on every filled role. 90-day retention improves as onboarding automation drives consistent ramp — quality of hire follows.
Ranges reflect published 2026 benchmarks (SHRM, Humanly, Pin, MokaHR, AIHR Institute, TheHireHub) and Alterra AI portfolio deployments in SaaS, professional services, and light-industrial mid-market companies.
Sources: SHRM 2025 Cost-per-Hire Benchmark ($5,475 avg non-executive), Pin AI Recruiting 2026 (14-day avg time-to-fill, 82% faster than industry), MokaHR (63% TTH reduction, enterprise cohort), TheHireHub (280% avg first-year ROI, 3,000+ projects), AIHR Institute (33% median TTH cut). Portfolio-wide rollouts realize an additional 40% cost efficiency vs. one-off deployments.
Candidate identification against role scorecards, then personalized outreach drafted for each candidate — pulling from public profile signals. Recruiters approve and send. Response rates typically double vs. template outreach because messages actually reference the candidate.
Every inbound application scored against the role scorecard. Ranked shortlist delivered to the hiring manager with reasoning. Recruiters spend their time on the top decile, not the bottom half. Adverse-impact analysis included by default for compliance.
AI-run scheduling for phone screens, panel interviews, and follow-ups. Handles time zones, reschedules, and interviewer availability. Candidate coordination cycle drops from 3–5 days to under 24 hours. Recruiter admin drops to near zero.
New-hire paperwork, account provisioning, equipment ordering, 30/60/90 check-in scheduling. First-week structured plan with role-specific ramp milestones. 90-day retention improvement follows from consistent, structured onboarding — not from luck.
48-hour deep dive on the last 12 months of hiring.
Front-of-funnel first.
End-to-end for the pilot role.
Roll out to all open reqs. Measure.
Ranges reflect typical outcomes for portfolio companies hiring 30–120 roles per year across sales, engineering, and operations, running Greenhouse / Lever / Ashby / Workable. Portfolio-wide rollouts standardize hiring KPIs across every portfolio co.
Get the assessment →US average is ~42 days. AI cuts it 50–70% for most roles. Leading platforms report 14-day averages — 82% faster than industry. Biggest gains: sourcing and scheduling. Screening AI produces smaller, consistent gains. Roles with heavy panel interviews compress less because interview capacity, not sourcing, is the bottleneck.
US average CPH is $5,475 (SHRM 2025). AI recruiting typically reduces CPH 30–40%. Mature implementations hit 65%+ when vacancy-cost reduction from faster TTH is included. Portfolio companies filling 30–100 roles/yr see six-figure annual savings from the recruitment stack alone.
Bias risk is real and must be managed. Well-built AI reduces some human biases (fatigue, primacy/recency, resume-format effects) while requiring audit of training data and criteria to avoid encoding historical bias. Our builds require adverse-impact analysis on every scored pool, human review of AI-suggested rejects, and periodic third-party audits. Done right, AI-augmented screening improves diversity by standardizing evaluation.
Deploys inside the existing ATS (Greenhouse, Lever, Workable, Ashby) or against LinkedIn Recruiter and calendaring tools. Scoped end-to-end deployment runs 3–5 weeks. First AI-assisted hire typically closes 2–3 weeks after go-live. Steady-state metrics stabilize by end of Q1.
Same team, 3–5x throughput. Recruiters stop doing sourcing spreadsheets, cold outreach drafting, calendar coordination, and screening admin — and start doing the parts that require judgment: candidate advocacy, hiring manager consultation, close negotiations. Portfolio companies rarely reduce recruiter headcount post-AI because there's always more hiring to do.
48-hour AI opportunity assessment. Ranked by EBITDA impact. Delivered before the next partner meeting.
Book an assessment →Response within 1 business day. Fixed-scope, fixed-fee engagements.