Ethos raises $22.75M from a16z for its expert network with voice onboarding

When companies are looking for opinions or advice on a project, they tend to go to LinkedIn or use expert networks like GLG, Third Bridge, or Alphasights. But they often do not find high-quality entries, despite their searches.

Today, these sites ask experts to fill out a form based on their job title, which is then used to match them with companies that need their help.

Ethos, based in London, believes that artificial intelligence can improve both aspects of this experience. For experts, it provides an audio setting to ask a wide range of questions and get more data about their knowledge in different areas not covered by their job titles. For businesses, Ethos can better match the natural language queries these organizations ask to their project, thanks to the broader range of data it has collected.

Ethos said its voice and data onboarding system allows it to answer complex customer questions like, “Find people who have worked at a startup funded by A-list investors working on a finance automation solution.”

Another example given by the startup is how a pharmaceutical company using its platform can search for doctors who specialize in a particular field, but have also written research papers on that topic or have an understanding of drug development.

Ethos today announced a $22.75 million Series A round led by a16z with participation from General Catalyst, XTX Markets, Evantic Capital, and Common Magic.

Aneesh Acharya of a16z believes that legacy platforms like LinkedIn and GLG only show superficial signs with job titles. He believes Ethos captures different subspecialties through its audio interview process with curated questions.

“I think voice is the original form of human communication. Most people, you know, most people don’t know how to write their story in a very concise, compelling, precise way. Voice is a huge unlock for Ethos,” Acharaya told TechCrunch over a phone call.

How Ethos scales its network

Ethos was founded by James Lu and Daniel Mankiewicz in 2024. Lu previously worked at McKinsey and later at Softbank, where he worked to transform companies like WeWork and Arm. Mankiewicz worked as an AI researcher at DeepMind, where he worked on YouTube’s video compression algorithm, Gemini, and AlphaDev sorting algorithm.

Both founders came to approach the problems of building an expert network from different angles. Lu always wanted to work on providing economic and job opportunities for people. Mankiewicz believes that the economy is a knowledge graph of people, companies, and products, and with the right algorithms, you can match these entities to each other.

“Traditional expert platforms focus almost purely on a combination of job titles and job descriptions,” Lu said. “What we notice is that most clients and most employers are not looking for a company with job titles. They are looking for a specific skill and a specific ability. We also noticed that over time, the search for skill and ability will gradually merge between the human economy and the agent economy.”

In addition to data provided by experts, Ethos also looks at other public sources such as blogs and academic research, along with social links to match businesses with the right people.

The company also conducts interviews through its platform using voice agents and extracts insights. Startups like List Labs and Outset already provide a way for companies to use conversational AI for interviews, providing some competition on this front. But Ethos believes its network of experts is better suited to particular clients than its competitors.

Ethos did not mention its client base, but said that top hedge funds, private equity firms, leading institutional AI labs, and enterprise consultancies were already using its product. 30% or more is taken as a fee for each project from companies, depending on the nature of the project. The company indicated it was on track to achieve “eight-figure annual revenues” but did not provide specific numbers.

He also did not say how many experts are on the platform, but said that approximately 35,000 people join each week. (The spirit sends invitations to people who it thinks can benefit from it.)

One of the challenges facing the startup is growing an expert user base relevant to its customers. The company said AI labs spending money to map human talent helped its cause.

“Our view here is that AI labs are pointing a huge capital cannon at every economically valuable profession in the world. They’re trying to map every profession. That’s an amazing tailwind for us,” Lu said.

He noted that these labs are building professional services in the fields of law, health, finance, and management, so they want all kinds of experts in these networks to build their models and get feedback on their products and strategies.

The company now has eight people on its team, and its goal is to keep the team together as it expands.