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Alex: Your AI Recruiting Partner

Alex is an AI recruiting partner that automates busywork for recruiters, including phone screens, video interviews, note-taking, and more. The company recently raised a $17M Series A led by Peak XV Partners and already serves Fortune 100 companies, nationwide restaurant chains, and Big 4 accounting firms. In this interview with YC's Nicolas Dessaigne, co-founders Aaron Wang and John Rytel share their journey from building apps together in college to scaling one of the fastest-growing companies in recruiting. They talk about why it takes hundreds of applications to find that next job, what tools candidates are using to cheat in interviews, and how AI agents represent the future of how job seekers will find their next opportunities in days, not months. Chapters: 00:00 – Intro 00:35 – What Alex Does for Recruiters 02:00 – From College Projects to Starting Alex 03:50 – Why Recruiting Is Broken Today 05:40 – Automating Busywork in Hiring 08:00 – Customers: Fortune 100s, Restaurants & Big 4 Firms 10:10 – Why It Takes Hundreds of Applications to Get Hired 12:40 – Candidates Cheating with AI Tools 15:00 – Scaling One of the Fastest Growing Recruiting Startups 17:30 – AI Agents and the Future of Job Hunting

NDNicolas DessaignehostAWAaron WangguestJRJohn Rytelguest

Sep 29, 2025·21m·Watch on YouTube ↗

📖 CHAPTERS

1. 1

   Alex in one sentence: an autonomous AI recruiting partner

   Nicolas introduces Aaron Wang and John Rytel and the company’s recent $17M Series A. Aaron gives the crisp product definition: Alex is an AI recruiting partner that can run key recruiting workflows end-to-end.

2. 2

   What Alex automates: sourcing, screening, interviewing, scheduling, ATS updates

   The founders explain what Alex does day-to-day for recruiters and staffing firms. The agent connects to existing recruiting systems and executes repetitive tasks that consume recruiter bandwidth.

3. 3

   Why recruiting is broken: application volume surge and slow time-to-hire

   Aaron argues the hiring market has become dramatically less efficient: more applicants, longer cycles, and limited recruiter capacity. Alex targets both the bandwidth bottleneck and the matching problem using data and scalable interviews.

4. 4

   Scale and traction: thousands of interviews per day, tens of thousands of open roles

   They quantify usage and deployment maturity since launch. Alex is already running large volumes of interviews daily and supporting hiring across many active requisitions.

5. 5

   Who uses Alex and why staffing agencies were the wedge

   Aaron explains the go-to-market: staffing agencies pulled hardest because incentives align and pain is concentrated. They also support very large employers across diverse job families.

6. 6

   Role depth and customization: testing skills and learning from ATS + intake notes

   The conversation digs into how Alex can screen for niche qualifications (like nuclear welding) and assess technical skill early. Alex uses internal company context (ATS history, job descriptions, hiring manager notes) and can be tuned per role.

7. 7

   Origin story and timing: candidate-first insight and GPT-4 Turbo enabling voice agents

   They trace the idea to their experience as candidates and earlier hiring-tech experimentation at Brown. Building became feasible when conversational AI/voice latency improved in late 2023, leading to a 2024 build and launch.

8. 8

   Making AI interviews feel natural: low latency, orchestration, guardrails, and naming

   John describes the technical work to escape the “uncanny valley”: orchestrating multiple models for low-latency voice, improving transcription and voice quality over time, and adding guardrails so interviews stay structured. Aaron shares a practical reason for the name “Alex”: transcription reliability.

9. 9

   Adversarial candidates: prompt injection, AI cheating, and deepfake detection

   They discuss how candidates try to “hack” interviews, especially engineers, and how the product defends against abuse. The arms race includes mass applying with AI tools, using real-time AI “overlays,” and even live deepfakes in video interviews.

10. 10

    Fixing the job hunt: everyone gets a first interview and ghosting drops

    Aaron and John outline a candidate-centric future: applications should reliably yield an initial conversation. They argue AI can democratize access to opportunity, reduce ghosting, and help candidates get updates and answers throughout the process.

11. 11

    Proof it works: resurfacing hidden talent, stack-ranking, and retention improvements

    They give a concrete example where Alex mined an existing ATS database to find scarce COBOL candidates and quickly placed them. Success metrics include whether Alex’s rankings match or beat recruiters, plus downstream retention and staffing revenue outcomes.

12. 12

    Series A, rebrand, and building trust with enterprises

    Aaron explains raising now due to market pull and the need to be best-in-class for enterprise HR buyers who’ve been burned by past tech. They also discuss the rebrand from Apriori to Alex because customers already used that name and it felt more approachable.

13. 13

    Five-year outlook: recruiters supercharged, humans focus on relationships; founder lessons

    They argue AI won’t replace recruiters but will remove repetitive admin work so recruiters can focus on closing candidates and partnering with hiring managers. They close with hiring plans and advice: hold strong vision while staying flexible as models and tools evolve quickly.