LinkedIn and legacy expert networks like GLG rely on a brittle matching system: job titles and form fields. The result, according to Ethos, a London-based startup that just closed a $22.75 million Series A led by a16z, is that companies looking for specialized advice often find shallow matches.
Ethos replaces that with voice-powered onboarding. Instead of asking experts to fill a form based on their title, the platform conducts voice interviews with curated questions—extracting knowledge across domains that job titles don't capture. For clients, this means richer queries: a pharma company can search for doctors in a specialty who have also published papers on the subject, or a hedge fund can find people from A-grade funded startups working on finance automation.
The mechanism is straightforward in principle. Voice interviews capture more nuanced expertise than structured forms. Ethos pairs that data with public signals—academic papers, blogs, social links—to build a more complete profile of each expert's capabilities. The company also uses voice agents on its own platform to conduct research interviews and extract further insights.
Founded in 2024 by James Lo (formerly McKinsey and SoftBank, where he worked on transformations of WeWork and Arm) and Daniel Mankowitz (an AI researcher at DeepMind who worked on YouTube's video compression, Gemini, and the AlphaDev sorting algorithm), Ethos is attacking the problem from two angles. Lo focused on economic opportunity and employment matching; Mankowitz approached expertise as a knowledge graph of people, companies, and products to be algorithmically aligned.
The traction is early but substantial. Ethos reports onboarding roughly 35,000 experts per week (through targeted invites). The platform is already serving top hedge funds, PE firms, leading AI labs, and enterprise consulting shops, taking 30% or more per project depending on scope. The company is on track for eight-figure annualized revenue but hasn't disclosed specific figures.
Competition exists—startups like Listen Labs and Outset already offer conversational AI for interview workflows. But Ethos bets its network advantage matters: AI labs are actively spending to map human talent across professions (law, health, finance, management) to build and validate their models. That tailwind, Lo argues, benefits any platform capturing expert knowledge at scale.
The team remains intentionally lean—eight people—with a focus on scaling the network without proportional headcount growth. The a16z round, joined by General Catalyst, XTX Markets, Evantic Capital, and Common Magic, funds that approach.