Humanly vs Ashby
Side-by-side comparison of AI visibility scores, market position, and capabilities
Seattle AI recruiting platform processing 250K candidate interviews monthly with 600M+ profile database; YC W20 $24-30.6M with Teamable/Sprockets/Qualifi/HourWork acquisitions competing with Paradox and HireVue for talent acquisition automation.
About
Humanly is a Seattle-based AI recruiting and talent acquisition automation platform — backed by Y Combinator (W20) with $24-30.6 million raised in total funding from Drive Capital, Zeal Capital, Spark Growth Ventures, Alumni Ventures, and YC including a $7 million round in May 2025 — providing companies with AI-powered candidate screening, video interview automation, interview scheduling, reference checks, and talent sourcing from a database of 600+ million candidate profiles, processing approximately 250,000 candidate interviews per month for customers across retail, healthcare, logistics, and professional services verticals. Humanly has expanded through acquisition: Teamable (employee referral automation, May 2024), Sprockets (hourly workforce screening), Qualifi (interview intelligence), and HourWork (hourly worker retention, October 2025) collectively build a comprehensive talent acquisition platform from sourcing through retention.
Ashby is a modern ATS for high-growth tech companies built on deep recruiting analytics, integrated CRM sourcing, and automated scheduling; known for transparent published pricing targeting Series A–D tech companies.
About
Ashby is a modern applicant tracking system (ATS) and recruiting platform designed for high-growth technology companies, combining scheduling automation, analytics, and structured interview workflows in a single system. Founded in 2018 and headquartered in San Francisco, Ashby was built from the ground up to serve companies that have outgrown simpler tools like Lever or Greenhouse's entry-level tiers, with a particular focus on deep analytics that let recruiting leaders measure pipeline efficiency, source quality, and interview process performance.
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