Mercor vs Perfect

Workable is an agentic recruiting and HR platform. A native AI agent sources passive candidates from 400M+ profiles, screens every applicant against your job criteria and builds vetted shortlists inside a complete ATS, while onboarding, performance, time off, employee records and reporting run on the same system of record.

KI-gestütztes ATS + CRM, das den gesamten Recruiting-Desk an einem Ort führt

SpezialisiertSupplies enterprise AI training data and expert model evaluations, operating on the infrastructure side of AI labs.

Vermittelt Software-Fachleute über Arcs Marktplatz für geprüfte Remote-Talente mithilfe von KI-Kandidatenabgleich.

Das KI-native ATS, das Ihren gesamten Recruiting-Stack ersetzt

Manatal is an AI recruitment platform combining an applicant tracking system, recruitment CRM and AI sourcing, screening and interview tools for agencies and in-house hiring teams.

Sense is an AI-powered talent engagement platform that automates candidate communication, interview scheduling, screening and matching for talent acquisition and staffing teams.

Autonomes Hiring mit agentischer KI

Ein KI-Recruiter, der Bewerber interviewt, verifiziert und vorfiltert

SpezialisiertCombines human expert technical interviewers with AI screening for rigorous engineering candidate evaluation.

Pitch N Hire is an AI-native recruitment platform that joins a full applicant tracking system with HRMS, payroll and staffing services on one shared candidate-to-employee record. Prebuilt hiring agents source, screen, schedule and draft offers, while HRMS modules pick the same person up for onboarding, attendance and payslips.

Humanly is an AI recruiting platform built for high-volume, frontline and hourly hiring. It engages every applicant across chat, SMS, email, voice and video, screens candidates through structured conversations instead of keyword resume scans, runs AI interviews around the clock, and schedules the next step automatically, then hands recruiters a ranked shortlist with transcripts and reasoning behind each recommendation.