Ethos is a London startup building an AI expert network that helps companies find and vet specialists faster than LinkedIn or old-school expert-call firms. On May 6, 2026, it raised a $22.75 million Series A led by a16z. The problem it’s chasing is obvious once you see it: job titles are a lousy proxy for real capability when a client needs someone with weirdly specific experience. Ethos was founded in 2024 by James Lo and Daniel Mankowitz, and its bet is that voice data can capture expertise a résumé never will.
What is Ethos and how does the AI expert network work?
Here’s the basic workflow. A customer writes a natural-language brief describing the exact kind of person they need. Ethos searches across 500 million-plus profiles and reaches prospects through a network with more than 1 million warm connections. It screens people with an AI voice agent, then turns interview transcripts into research outputs using public filings, commercial datasets, and more than 5 million academic papers.
The expert side is where Ethos tries to look different. Instead of asking people to fill out a static form and hope their title says enough, the platform runs voice-based onboarding to pull out sub-specialties and adjacent experience. It also captures domain nuance that usually gets lost. That’s why the company says it can handle odd but realistic requests — like operators from finance-automation startups backed by top-tier investors, or doctors in a narrow field who also publish research and understand drug development.
A lot of manual work disappears if that works. Traditional expert networks still rely on recruiters doing profile searches and sending outreach. They also screen for fit, book calls, check compliance, and package notes for the client. Ethos is trying to compress all of that into one workflow so the buyer can move from “I need this exact kind of person” to a usable conversation and written output without juggling five tools and a pile of coordinators.
There’s more. Ethos says its AI interviewer can run long-form conversations of up to 60 minutes, and some experts can join without the usual scheduling back-and-forth. That makes the product feel less like a directory and more like a research system with expert sourcing built in.
Who founded Ethos, and how is the AI expert network growing?
The founding story
Ethos was founded in London in 2024 by CEO James Lo and CTO Daniel J. Mankowitz. Lo came at the idea from the labor side — he has said he wanted to create better economic and work opportunities for people. Mankowitz saw the economy more like a knowledge graph of people, companies, and products, where better matching could create more value. Put differently, both founders thought the market cared too much about titles and not enough about actual capability.
Why the founders fit this market
Lo’s background is unusually practical for this kind of company. Before Ethos, he worked at McKinsey and later at SoftBank, where he was involved in transformation work around companies including WeWork and Arm. That matters because expert networks are really a service business disguised as software. You need to understand buyers, operations, and high-stakes research workflows.
Mankowitz brings the harder technical edge. He worked as an AI researcher at DeepMind on YouTube video compression, Gemini, and AlphaDev. AlphaDev is the project that discovered faster sorting algorithms, and Mankowitz was one of the named researchers on that work. That doesn’t automatically make someone good at enterprise software. But it does explain why Ethos treats interviews, matching, and expert data as machine-readable problems instead of staffing problems.
Early traction and economics
Ethos isn’t naming customers yet, but the product is already used by top hedge funds, private equity firms, leading foundational AI labs, and enterprise consulting clients. The network is growing fast too, with roughly 35,000 people joining each week through an invite-led model. Ethos takes 30% or more as a per-project fee, depending on the work, and is already tracking toward eight-figure annualized revenue. The whole team is still just 8 people. Probably both.
Funding details
The new round is a $22.75 million Series A led by a16z, with General Catalyst, XTX Markets, Evantic Capital, and Common Magic also participating. The raise was announced on May 6, 2026. Ethos hasn’t publicly laid out a detailed capital plan, but the timing is clear enough: it now has the money to keep building product while scaling the network behind it.
Where Ethos sits against incumbents and newer tools
The incumbents are easy to name: LinkedIn for discovery, then expert networks like GLG, Third Bridge, and AlphaSights for paid access. Those businesses still do plenty of volume, but the old model depends heavily on titles, recruiter judgment, and manual coordination. Ethos’s pitch is that these are shallow signals, and that a structured voice interview produces a much richer profile of what someone actually knows.
The newer comparison set is messier. Listen Labs and Outset use AI moderators to run interviews at scale, mostly for customer or user research rather than expert-network sourcing. NewtonX mixes AI with custom recruiting for B2B research and expert work. Tegus leans hard into expert-call transcripts and investor research. Ethos is trying to splice pieces of all those categories together. It combines expert discovery and AI-led screening. It also folds in AI-led interviewing and synthesized research outputs in one stack. It layers in public signals from blogs, academic papers, and social links, which gives it a broader matching graph than a résumé-only system.
Why are investors betting on AI expert networks now?
a16z’s thesis here is pretty direct. The firm argues that legacy platforms expose only thin signals, while voice interactions can surface sub-specializations people rarely write down well. That matters even more in regulated or high-consequence settings, where accuracy, context, and compliance all matter.
Ethos also isn’t just selling to firms that want a better expert call tomorrow morning. It’s showing up at a moment when AI labs are spending real money to map human expertise, collect feedback from professionals, and build products for law, health, finance, and management work. That makes Ethos interesting to investors for a bigger reason: it could become part expert network, part data-collection layer, part research workflow for AI-native companies.
How big is the expert network market in 2026?
This isn’t some tiny corner of finance anymore. Inex One pegged the global expert-network industry at more than $2.5 billion in 2024 and around $3 billion in 2025, after years of steady expansion. That growth has come from the same basic pattern: more firms want primary research fast, and they’re willing to pay for real practitioners instead of relying only on published reports or generic survey panels.
The structural shift is buyer behavior. Expert networks used to be associated mostly with investors and consultants. Now the demand base is wider — product teams, enterprise strategy groups, and AI labs all want direct access to people who’ve actually done the work. Voice AI also changes the math. If screening and interviewing can happen faster, with better compliance controls and lower coordination costs, the old expert-call workflow starts to look pretty clunky. That’s the opening Ethos is chasing.
Final take on Ethos
Ethos is betting that the future of the AI expert network won’t look like a better directory. It’ll look like a full research engine built around voice, structured expertise, and fast synthesis. The funding gives the company room to prove that idea at a bigger scale, but the real test is still ahead: whether it can keep quality high and compliance tight as it expands into more specialized, regulated categories.
Read how BigEndian Semiconductors raised $6M in pre-Series A funding led by IAN Alpha Fund to commercialise its secure system-on-chips for surveillance, IoT, telecom, and enterprise hardware, targeting growing demand for specialised edge AI silicon with built-in security and production-ready design.
FAQ
– What funding did Ethos raise?
Ethos raised a $22.75 million Series A on May 6, 2026. a16z led the round, and General Catalyst, XTX Markets, Evantic Capital, and Common Magic also joined.
– How does Ethos work as an AI expert network?
Ethos lets companies describe the expertise they need in plain language, then uses AI to find, contact, screen, and interview matching experts. The platform searches more than 500 million profiles, uses over 1 million warm connections for outreach, and can turn interviews into research reports after the call.
– Who are the founders of Ethos?
Ethos was founded in 2024 by James Lo and Daniel J. Mankowitz. Lo previously worked at McKinsey and SoftBank, while Mankowitz came from DeepMind, where he worked on projects including Gemini and AlphaDev.
– Why is Ethos part of the expert network market?
Because its core business is still matching companies with qualified people for paid insight, research, and interviews. What makes it different is the AI layer: Ethos uses voice onboarding and automated interviews to modernize a market that industry estimates place at roughly $3 billion in 2025.
