Metaview wants recruiters to spend less time doing repetitive hiring work and more time directing the AI systems doing it for them.
The recruiting technology company said Wednesday that Insight Partners led its Series C, with participation from GV, Intrepid Growth Partners, Seedcamp, Vertex Ventures US, Plural and Garuda Ventures. The latest round brings Metaview’s total funding to $110 million.
Founded in 2018 by former Uber and Palantir employees Siadhal Magos and Shahriar Tajbakhsh, Metaview now serves more than 7,000 companies, including Deel, Affirm, Navan and Replit.
The company plans to use the money to expand its AI recruiting platform, bring its autonomous recruiting coworker, fillmore, to general availability, open a New York office and grow its workforce from 80 to 250 employees by the end of 2027.
From interview notes to AI recruiting agents
Metaview started by capturing interviews and says it has processed more than 6 million conversations. It now uses that accumulated context to power AI agents across sourcing, application review, screening, and interview documentation.
Its newest offering, fillmore, is an autonomous recruiting coworker that can research candidates, build target lists, write personalized outreach, follow up with prospects and schedule screening calls. The company says humans remain responsible for setting hiring criteria and making final decisions.
“The best engineering teams have already moved from writing code by hand to orchestrating AI agents that do the work. Recruiting is next,” Magos said in the company’s announcement.
Metaview is betting on application overload
Metaview is positioning its agents as a response to rising recruiting volume. Magos said applications per recruiter have increased 412%, while the company cites an average time-to-fill of nearly 45 days.
According to Metaview, some customers using its tools have reduced time-to-hire by more than 75%, although results will vary depending on role, hiring process and how extensively the platform is used.
The appeal is straightforward: AI agents can research, sort and follow up with candidates at a scale that would be difficult for human recruiting teams to match manually. The harder question is whether speeding up those workflows also improves the quality of hiring decisions.
What the funding means for employers
For employers, the biggest potential change is not simply faster individual tasks. An agent-based system could allow recruiting teams to keep sourcing, screening and following up outside normal working hours, creating a more continuous hiring process.
But greater automation also makes oversight more important. Recruiting decisions can affect careers, so systems that process applications or conduct screenings still depend on the quality of the criteria humans provide and the information agents use.
Metaview’s model of keeping people responsible for final decisions addresses part of that concern, but it does not remove the need for careful review.
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How this affects job seekers
Candidates could see faster responses and screening, particularly when applications arrive outside traditional working hours. Metaview says screening can happen when it suits the candidate rather than waiting for a recruiter to become available.
There is another side to that speed, however. When AI handles more of the initial filtering, candidates may have fewer opportunities to explain their experience outside the criteria used by the system. That makes human oversight and clear hiring standards important as more recruiting decisions become automated.
Metaview plans to add more specialist agents, including a dedicated AI screening agent, while expanding its 10x Recruiting training program for talent professionals.
Its broader bet is that recruiting teams will increasingly supervise AI systems that handle sourcing, screening and coordination rather than performing each task themselves. If that model takes hold, the recruiter’s job may shift from running the hiring workflow to managing the agents that run it.
Other news: Microsoft is redesigning Copilot around Home, Code, and Autopilot, bringing everyday AI tasks, natural-language app building, and persistent agents into a more unified experience.