Juicebox raises $80M Series B at $850M valuation to power passive AI recruiting for 5,000 companies

Summary

Juicebox, an AI-powered passive recruiting platform, raised an $80M Series B led by DST Global, with participation from Sequoia Capital and Y Combinator, valuing the company at $850M. Total funding now stands at $116M.

A year ago the company had four employees. It reached 13 by its Series A and now has 40 people. ARR has tripled since the Series A, and the platform serves over 5,000 customers.

What the platform does

Juicebox focuses exclusively on passive talent sourcing, crawling the web to identify candidates who are not actively job hunting, stack-ranking them against a given role, and automating outreach via email sequences. CEO David Paffenholz argues that drawing from the entire web scales cleanly alongside customer growth.

The platform has two commercial tiers. A per-seat license lets recruiters log in and run searches manually. An agent tier operates on a per-job basis, deploying autonomous agents that surface profiles and send outreach daily without human check-ins.

Customer mix

The customer base has moved beyond its early Silicon Valley startup concentration. Large defense contractors and financial institutions now sit alongside venture-backed tech companies, drawn by the same pressure. AI-generated application spam has degraded inbound hiring quality to the point where outbound sourcing is increasingly the only reliable channel. Role coverage has expanded accordingly, from a heavy weighting toward software engineering to sales, HR, and finance.

Paffenholz argues that passive outbound will eventually become the default for all hiring, not just tech. The more companies compete for the same talent, the more they go after people who are not looking.

GitHub as a candidate signal

For candidates wanting to surface in Juicebox searches, Paffenholz points to GitHub as the most underexploited channel. Historically difficult for recruiters to parse, GitHub data has become significantly more indexed and searchable over the last six to twelve months. Contributions to open-source repos and other activity signals are now being used actively to identify passive candidates. LinkedIn and personal websites remain useful, though personal sites are still rare enough in the candidate population that they represent marginal reach. Publishing more, whether a current role, active projects, or outside interests, increases the chance of appearing as a match.