Moonhub is an AI recruiter that searches a vast talent pool, identifies strong fits, and engages candidates so companies can hire faster with better matches.
Moonhub combines a large talent data platform with agents that work like a sourcing team. Describe the role in plain language and its models identify candidates whose experience signals fit, including people who would never match a keyword search. The system then handles outreach, follow-ups, and scheduling, presenting hiring managers with a curated shortlist rather than a raw search export. Human recruiters stay in control of judgment calls while the AI handles the volume work.
Because the agents handle sourcing volume, recruiters spend their hours on conversations and judgment calls. The plain-language search is the piece users remark on: describing a hire the way you would to a colleague yields better candidates than boolean strings, especially for passive talent.
Because agents handle sourcing volume, recruiters spend their hours on conversations and judgment. The plain-language search is what users remark on: describing a hire as you would to a colleague surfaces better candidates than boolean strings, especially among passive talent who never visit job boards.
Candidate data is refreshed continuously, so outreach references current roles and achievements rather than stale profiles. The collaborative shortlist review keeps hiring managers engaged without turning the process into another meeting series.
Moonhub works with companies through commercial agreements tied to hiring plans; pricing is arranged with the team.
Startups and growth companies that need recruiting capacity without expanding the in-house sourcing team. It fits growth companies that need recruiting leverage without adding headcount.
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