
HireX
Deploy autonomous AI agents to automate your entire hiring
I built HireX because I got tired of watching teams drown in CVs, ATS toggling, and “AI‑assisted” tools that still required manual work. Instead of another chat‑based recruiter assistant, I wanted to build a true agentic hiring OS: 27 specialized AI agents that automate sourcing, outreach, qualification, and basic negotiation—so founders and hiring managers can focus on closing the right people, not sorting resumes.
HireX lives at https://gethirex.space/. It’s a B2B SaaS platform where each agent owns a slice of the hiring workflow:
One agent scours LinkedIn, niche job boards, and your own pipeline.
Another parses and ranks candidates based on skills, intent, and fit signals.
One more runs outbound sequences and handles early‑stage conversations.
We monetize via subscriptions (per‑team plans), and we’re currently VC‑funded after a seed round that let us scale the multi‑agent architecture. The big bet is that AI hiring should be a system, not a feature—and that if you really automate the full funnel, you can cut time‑to‑hire by 70% while keeping quality high.
If you’re building agentic infra, HR tech, or multi‑agent workflows, I’d love to hear:
What’s your biggest blocker with reliability and hallucination in agent‑driven products?
About
I built HireX because I watched hundreds of teams drown in manual screening, bloated ATS flows, and missed talent signals. Instead of another “AI‑assisted” ATS, I wanted to build a true agentic hiring OS: 27+ AI agents t

2 Comments
It is a significant leap for HR tech to move from "search filters" to "autonomous agents" because most platforms still require a human to manually approve every single outreach email which often creates the very bottleneck the software was supposed to fix.
The real strength of a 27-agent architecture is the modularity because having a specialized agent for "intent signals" separate from "qualification" allows the system to cross-reference data points—like a candidate's recent GitHub activity versus their LinkedIn profile—to determine true fit before a human ever needs to intervene.
Since you are running a multi-agent workflow at this scale how are you managing the "handoff" logic between agents to ensure that a candidate's specific context from an early-stage outreach conversation isn't lost or misinterpreted when they are moved to the negotiation agent?
Hey congrats! What's your monthly churn rate?