Perfectly

Product & Competitive Intelligence

AI recruiting agent that fills roles in 2-4 weeks with 2x higher interview pass rates.

Company Overview

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.

Competitive Advantage & Moat

Product Roadmap & Public Announcements

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.

Signals & Private Analysis

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.

Product Roadmap Priorities

Recommender-based talent matching
Improving
Product Differentiation
Product

AI-powered candidate-role matching using recommender system architectures adapted from social media content feeds to predict candidate success and interview pass likelihood.

In Plain English

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.

Analogy

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.

Infinite-context candidate modeling
Improving
Operational Efficiency
Data

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.

In Plain English

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.

Analogy

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.

Conversational AI screening agents
Improving
Cost Reduction
Operations

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.

In Plain English

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.

Analogy

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.

Company Overview

Key Team Members

  • Victor Luo, Co-Founder
  • Zhuang "Gary" Luo, Co-Founder
  • Huimin Xie, Co-Founder

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.

Funding History

  • 2025 | Victor Luo, Zhuang "Gary" Luo, and Huimin Xie found Perfectly.
  • 2026 | Accepted into Y Combinator Winter 2026 batch.
  • 2026 | Operating in private beta with early customers (Giga, Corgi, LlamaIndex, Porter, Mintlify).

Competitors

  • AI Recruiting Platforms: Moonhub, Juicebox (AI sourcing), Mercor, Paraform.
  • Traditional Recruiting Agencies: Robert Half, Hays, Kforce (human-led).
  • ATS-Integrated AI Tools: Lever AI, Greenhouse AI features, HireVue (screening).
  • Sourcing Automation: hireEZ, Gem, SeekOut.