When companies are looking for feedback or advice on a project, they go to LinkedIn or use expert networks like GLG, Third Bridge or Alphasights. But despite their search, they often don’t find quality input.
Today, these sites ask professionals to fill out a form based on job titles, which are then used to match them with companies that need their help.
It is located in London ethos AI thinks it can improve both aspects of that experience. For professionals, it offers voice-activated recruitment to ask a wider set of questions and learn more about their knowledge in different areas not covered by their job titles. Ethos for companies can better match the natural language requests these organizations make for their projects thanks to the broader data it collects.
Ethos said its voice-based onboarding and data enable it to answer complex customer questions, such as “Find me people working at an A-backed startup solving financial automation.”
Another example the startup gave was how a pharmaceutical company using its platform could search for doctors who specialize in a certain area but have written articles on the subject or have an understanding of drug development.
Today, Ethos announced a $22.75 million Series A round led by a16z with participation from General Catalyst, XTX Markets, Evantic Capital and Common Magic.
Anish Acharya of a16z believes that legacy platforms like LinkedIn and GLG are only showing shallow signals with job titles. He believes that Ethos captures the various subspecialties through an audio interview process with selected questions.
“I think voice is the primordial form of human communication. You know, most people don’t know how to write their stories in a very concise, compelling, and precise way. Voice is a huge key to Ethos,” Acharya told TechCrunch during a call.
How Ethos is expanding its network
Ethos was founded in 2024 by James Lo and Daniel Mankowitz. Lo previously worked at McKinsey and later at Softbank, where he worked on the transformation of companies such as WeWork and Arm. Mankowitz worked as an artificial intelligence researcher at DeepMind, where he worked on YouTube’s video compression algorithm, Gemini, and AlphaDev’s sorting algorithm.
Both founders came to solve the problems of building an expert network from different angles. Lo always wanted to work on providing people with the right economic and employment opportunities. Mankowitz thought that the economy is a knowledge graph of people, companies, and products, and using the right algorithms, you can match these entities with each other.
“Traditional expert platforms focus almost exclusively on a mix of job titles and job descriptions. What we have observed is that most customers and most employers are not looking for jobs. They are looking for specific skills and specific abilities. We have also observed that over time, the search for skills and abilities will gradually merge between the human economy and the agent economy,” Lo said.
In addition to information provided by experts, Ethos looks at other public sources, such as blogs and academic papers, along with social links to match companies with the right people.
The company also conducts interviews and elicits insights through its platform using voice agents. startups like Listen to the labs and The beginning is already offering some competition in the field by providing a way for companies to use conversational AI for interviews. But Ethos believes its network of experts is better suited for certain clients than its competitors.
Ethos wouldn’t name its customer base, but said top hedge funds, private equity firms, leading AI labs and enterprise consulting already use its product. Depending on the nature of the project, it charges businesses 30% or more per project fee. The company said it was on track for “eight-figure annual revenue,” but did not provide specific numbers.
He also didn’t say how many experts are on the platform, but said about 35,000 people join each week. (Ethos sends invitations to people they think might benefit from it.)
One of the challenges for a startup is to grow an expert user base that is relevant to its customers. The company said spending money on AI labs to map human talent is helping its cause.
“Our perspective here is that the AI labs have — they’re directing a huge gun of capital at every economically valuable occupation in the world. They’re trying to map every occupation. And that’s an amazing tailwind for us,” Lo said.
He noted that these labs build professional services in law, healthcare, 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 currently has eight people on its team and aims to keep the team compact while expanding.
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