The Expert Network Revolution: Why Ethos’ $22.75M Bet on Voice AI Might Just Change the Game
The world of expert networks is a fascinating, often overlooked corner of the business world. Companies spend billions annually seeking insights from specialists, yet the process remains clunky, inefficient, and surprisingly analog. Enter Ethos, a London-based startup that just secured $22.75 million in Series A funding led by a16z. What makes this particularly fascinating is their approach: leveraging voice AI to revolutionize how experts are matched with companies.
The Problem with Traditional Expert Networks
Let’s start with the elephant in the room: platforms like LinkedIn, GLG, or AlphaSights dominate the expert network space, but they’re built on a flawed foundation. Personally, I think the reliance on job titles as the primary matching criteria is a massive oversight. Job titles are shorthand, not substance. They tell you what someone does, but rarely how well they do it or the nuances of their expertise.
From my perspective, this is where Ethos sees an opportunity. By using voice-powered onboarding, they’re not just collecting data—they’re capturing the essence of an expert’s knowledge. One thing that immediately stands out is how this approach mirrors human intuition. When we assess someone’s expertise, we don’t just read their resume; we listen to them speak, observe their thought process, and gauge their depth of understanding. Ethos is essentially replicating this at scale.
Voice AI: The Secret Sauce?
What many people don’t realize is that voice communication is inherently richer than text. As a16z’s Anish Acharya pointed out, most people struggle to articulate their expertise in writing. Voice, however, is natural, nuanced, and immediate. This raises a deeper question: could voice AI be the key to unlocking a more accurate, human-centric way of matching talent with opportunity?
Ethos’ founders, James Lo and Daniel Mankowitz, seem to think so. Lo’s background in transforming companies like WeWork and Mankowitz’s AI expertise at DeepMind give them a unique vantage point. Their vision isn’t just about improving expert networks—it’s about redefining how skills and capabilities are mapped in the modern economy.
Beyond Job Titles: The Rise of Skill-Based Matching
Here’s where things get really interesting. Ethos isn’t just competing with LinkedIn; it’s challenging the very idea that job titles matter. In my opinion, this is a bold move. The traditional model assumes that companies want a “Chief Marketing Officer” or a “Data Scientist.” But what if they actually need someone who’s done something specific—like scaled a SaaS product in a regulated industry or built a predictive model for healthcare?
Ethos’ ability to answer complex queries like “Find me people who worked at a funded startup solving for finance automation” is a game-changer. It’s not just about matching titles; it’s about matching capabilities. This shift has massive implications for how we think about talent in the age of AI.
The AI Tailwind: A Hidden Advantage
A detail that I find especially interesting is Ethos’ positioning in the broader AI landscape. James Lo’s comment about AI labs “pointing a giant capital gun at every economically valuable occupation” is both provocative and insightful. What this really suggests is that as AI continues to map human expertise, platforms like Ethos will become increasingly valuable.
Think about it: if AI models need human feedback to improve, who better to provide it than the experts Ethos is aggregating? This isn’t just a tailwind—it’s a strategic advantage. While competitors like Listen Labs and Outset focus on conversational AI for interviews, Ethos is building a network that’s uniquely positioned to serve the needs of AI labs, hedge funds, and enterprise consultancies.
The Challenges Ahead
Of course, no revolution comes without hurdles. Scaling a relevant expert network is no small feat. Ethos claims 35,000 new experts join weekly, but relevance is key. Personally, I think their success will hinge on their ability to curate this network effectively. Too much noise, and the platform loses its value.
Another challenge is competition. While Ethos’ voice AI is innovative, it’s not entirely unique. Startups like Listen Labs are already in the space. What sets Ethos apart, in my opinion, is its focus on depth over breadth. They’re not just collecting voices; they’re extracting insights that traditional platforms can’t.
The Bigger Picture: Redefining Expertise in the AI Era
If you take a step back and think about it, Ethos is part of a larger trend: the democratization of expertise. In a world where AI is increasingly capable, human insight remains irreplaceable—but only if it’s accessible. Ethos is betting that voice AI is the bridge between niche expertise and global demand.
What this really suggests is that the future of work isn’t just about skills; it’s about how those skills are discovered, validated, and deployed. Ethos isn’t just building a platform; it’s reimagining the very concept of an expert network.
Final Thoughts
As someone who’s watched the expert network space for years, I’m intrigued by Ethos’ approach. Their use of voice AI feels like a natural evolution, not a gimmick. But here’s the provocative question: will this model scale? Will companies truly abandon job titles in favor of skill-based matching?
Personally, I think the answer is yes—but it won’t happen overnight. Ethos has a head start, but the real test will be whether they can maintain their edge as the market catches up. One thing’s for sure: the expert network space will never be the same. And that, in itself, is worth watching.
