
Technology
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Recruiting Automation
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YC W26
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Valuation:
Undisclosed

Last Updated:
March 24, 2026

Builds an AI-native recruiting agency powered by machine learning that automates sourcing, screening, and candidate delivery for startups and high-growth tech companies, replacing traditional recruiting teams with an AI agent ("Paul") that fills roles in 2-4 weeks with 2x higher interview pass rates.
Perfectly has publicly described its AI agent "Paul" for end-to-end recruiting automation, Slack-based candidate delivery, persistent evolving candidate profiles, and a hiring manager portal. Early customers include Giga, Corgi, LlamaIndex, Porter, and Mintlify. Success-based pricing (pay only when a role is filled). Geographic expansion from North America and Europe into Asia Pacific planned.
GitHub and hiring activity remain minimal, suggesting the founding team is handling all technical development internally. The founders' deep TikTok/Meta recommender system backgrounds suggest proprietary candidate-job matching models incorporating behavioral signals, latent skill inference, and outcome-based feedback loops. Expansion into technical assessment and interview scheduling automation is a logical next step.
AI-powered candidate-role matching using recommender system architectures adapted from social media content feeds to predict candidate success and interview pass likelihood.
The system works like a TikTok "For You" page but for hiring—instead of recommending videos, it recommends the best-fit candidates for each role by learning what "success" looks like from every past hire.
It's like Netflix recommendations, but instead of suggesting your next binge-worthy show, it finds the engineer who'll actually pass your system design interview.
Persistent, evolving candidate profiles that accumulate context across interactions, roles, and time—enabling the AI to build a living, longitudinal understanding of each candidate's capabilities and trajectory.
Instead of starting from scratch every time a candidate applies, the system remembers everything it's ever learned about them—like a recruiter with a perfect photographic memory who never forgets a conversation.
It's like having a CRM for humans that never forgets a detail—imagine if LinkedIn actually remembered that you pivoted from data science to ML engineering and stopped recommending analyst roles.
AI agent ("Paul") autonomously conducts deep intake interviews with hiring managers and screens candidates through conversational AI, replacing hours of human recruiter coordination with intelligent, adaptive dialogue.
The AI agent interviews both the hiring manager and the candidates so humans only spend time talking to people who are genuinely worth meeting—like a brilliant executive assistant who handles all the scheduling, vetting, and back-and-forth so you only walk into meetings that matter.
It's like replacing the world's most overworked recruiter with an AI that never gets tired, never forgets what the hiring manager said, and never accidentally ghosts a candidate because their inbox exploded.
All three co-founders built large-scale recommender systems at TikTok and Meta — the same ML architectures that power content feeds for billions of users — now repurposed to match candidates to roles with unprecedented precision and continuous learning from hiring outcomes.