AI has eliminated much of the friction that comes with applying for jobs, triggering a flood of applications that employers and hiring managers must now sort through to find top talent. Applications per recruiter are up 412%, and 72% of candidates now go 30 days or more without hearing anything back.
Recruiting teams have tried to absorb this influx in volume with the same headcount and tech stack, leading to longer open roles, strong applicants going unread, and recruiters spending their finite time sorting versus hiring. Where new tools have entered the market, they typically solve a single piece of the recruiting workflow – notetaking, screening, sourcing, etc. – but lack the context and memory to drive meaningfully better outcomes for teams.
A recruiting platform with shared memory
Metaview started as the purpose-built notetaker for interviews, built on the understanding that hiring decisions happen in conversations rather than the applicant tracking system: the intake call with a hiring manager, the interview itself, and the debrief afterward are all critical to understanding what “great” looks like for an employer. Every conversation sharpens a shared picture of the ideal candidate — a calibrated context layer shaped by real candidate feedback, skills signals, and the reasoning behind each hiring decision. Every tool on the platform draws from that same definition, so a correction made in one role carries across the organization.
Metaview puts that context to work across the full recruiting workflow. The intake call generates the role definition, so no one begins from a blank spec. Sourcing runs off that definition automatically, including against candidates already sitting in a company’s own database. Inbound applications are reviewed against the same standard, and interviews feed back into it. People continue to set the criteria and make all final decisions, but as the definition improves, agents can be trusted with more of the work, which is the bet behind fillmore, the autonomous recruiting coworker expected to arrive this fall.
Betting on the next generation of talent acquisition
The returns show up for both hiring teams and candidates. Companies using the Metaview platform have cut time to hire by more than 75% and are doubling their recruiting team’s output. Candidates also get faster answers, because the process can finally keep up with the volume.
Metaview becomes a company’s competitive hiring advantage – which we’ve heard firsthand across our own portfolio and in conversations with Metaview customers. Time saved in interviews was a key benefit, but what they saw as the true value was how much the accumulated context improved sourcing and application review downstream. Companies like Deel, Linktree, Affirm, Filevine, Replit, Honeycomb.io, and Wise now rely on Metaview, and the platform has captured over 6 million recruiting interviews to date.
Siadhal Magos and Shahriar Tajbakhsh started on this journey in 2018 well before the category had a name. Siadhal led product at Uber and Shahriar was a technical lead at Palantir. Our excitement in Metaview is only deepened by our conviction in their leadership and commitment to product innovation and development velocity.
Recruiting has been one of the last large enterprise workflows still running largely on individual memory and instinct – until now. We believe that success requires context to create differentiated hiring outcomes, and we’re thrilled to lead Metaview’s Series C alongside Siadhal, Shahriar, and the incredible team building the future of talent recruitment.
Metaview is an Insight Partners portfolio company.
