Ethos raises $22.75M Series A led by a16z for AI expert network

London-based Ethos has closed a $22.75M Series A led by a16z, with General Catalyst, XTX Markets, Evantic Capital, and additional investors participating. The pitch: rebuild the expert-network onboarding layer around voice and natural-language search, then sell better matching to clients who currently grind through LinkedIn and the incumbent networks.

The company argues that the standard form-based intake at GLG, Third Bridge, and AlphaSights captures job titles but misses the adjacent expertise that often determines whether an expert is actually useful on a given project. Ethos uses a voice-powered intake to surface a wider data set per expert, and lets clients query in natural language. One sample query the company highlighted to TechCrunch: "Find me people who worked at a funded startup by A-grade investors solving for finance automation." Another example: a pharma client searching for physicians in a specialty who have also published on the topic or worked in drug development.

The round size puts Ethos firmly in venture-scale ambition territory rather than as a niche tooling play. a16z leading a Series A in this segment is the more interesting signal than the dollar figure: the firm has not historically been a heavy investor in the expert-network category, which has been dominated by private-equity-style growth capital and strategic acquisitions (Bain Capital's stake in GLG, Leonard Green's investment in Third Bridge, AlphaSense's acquisition of Tegus).

What the product actually changes

The pitch separates two layers of the expert-network workflow. The first is expert intake and enrichment: who are you, what do you know, what adjacent domains do you have signal on. The second is client-side search and matching: a research analyst or strategy team posts a project and the network returns candidates.

Incumbents have historically optimized the second layer (large rosters, fast turnaround, compliance-vetted moderators) while the first layer is mostly a self-reported form plus a sourcing team's manual enrichment. Ethos is betting that voice intake produces structured data the form-based approach misses, and that better intake data unlocks better matching.

Whether that's true at scale is the open question. The expert-network business has historically been won on roster size, moderator relationships, and compliance posture, not on intake UX. A founder we'd want to ask: what's the retention curve on experts post-onboarding, and what's the match-quality lift versus a baseline GLG-style search on a controlled query set?

The round itself is fresh capital, not a market verdict. The category has absorbed several well-funded entrants over the last decade, and the incumbents have generally held share by acquiring, copying, or out-distributing the challengers. What to watch over the next two quarters: which named buy-side or consulting clients Ethos discloses, and whether the product's matching quality holds up against an AlphaSights or Third Bridge baseline on the same query.