When businesses need expert opinions or guidance on a project, they typically turn to LinkedIn or professional networks like GLG, Third Bridge, or Alphasights. Yet, despite their efforts, they often struggle to find high-quality insights. Currently, these platforms ask experts to fill out a form based on their job title, which is then used to match them with companies seeking assistance. London-based Ethos believes artificial intelligence can enhance both sides of this process. For experts, it offers voice-powered onboarding that asks a broader range of questions, capturing more data about their knowledge across various domains—information that job titles alone fail to reveal. For companies, Ethos can better match natural language queries submitted for their projects, thanks to the richer dataset it collects. Ethos claims its voice-based onboarding and data allow it to answer complex client requests like, “Find me people who worked at a funded startup backed by top-tier investors, solving for finance automation.”

Another example the startup provided involves a pharmaceutical company using its platform to search for doctors who specialize in a specific area, but who have also published papers on the subject or possess expertise in 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. a16z’s Anish Acharya believes that legacy platforms like LinkedIn and GLG only offer shallow signals based on job titles. He argues that Ethos captures different sub-specializations through its voice interview process, which uses curated questions. “I think voice is the original form of human communication. Most people don’t know how to write their story down in a very succinct, compelling, and accurate way,” Acharya said.

### How Ethos is scaling its network

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

Both founders approached the challenge of building an expert network from different perspectives. Lo always wanted to focus on providing the right economic and employment opportunities to people. Mankowitz believed that the economy is a knowledge graph of people, companies, and products, and with the right algorithms, these entities can be matched effectively. “Traditional expert platforms almost purely focus on a mixture of job titles and job descriptions. What we observe is that most clients and most employers are not looking for a job title or a company. They’re looking for a specific skill and a specific capability. We also observed that, over time, looking for a skill and capability is going to gradually merge between the human economy and the agent economy,” Lo said.

Beyond the data provided by experts, Ethos also examines other public sources like blogs and academic papers, along with social connections, to match companies with the right people. The company conducts interviews through its own platform using voice agents and extracts insights. Startups like Listen Labs and Outset already provide ways for companies to use conversational AI for interviews, offering some competition in this area. However, Ethos believes its network of experts is better suited for certain clients than its competitors. Ethos does not disclose its client base, but stated that top hedge funds, private equity firms, leading foundational AI labs, and enterprise consulting firms are already using its product. It charges a per-project fee of 30% or more from businesses, depending on the project’s nature. The company noted that it is on track for “an eight-figure annualized revenue” but did not provide specific numbers.

It also did not reveal how many experts are on the platform, but said that roughly 35,000 people are joining each week. (Ethos sends invites to people it believes can benefit from the platform.)

One challenge for the startup is growing an expert user base that remains relevant to its clients. The company noted that AI labs investing money to map human talent has been helping its cause. “Our perspective here is that the AI labs are pointing a giant capital gun at every economically valuable occupation in the world. They’re trying to map out every profession. So that’s an amazing tailwind for us,” Lo said. He explained that these labs are building professional services in areas like law, health, finance, and management, so they would want all kinds of experts in these networks to develop their models and receive feedback on their products and strategies. The company currently has eight people on its team, and its goal is to keep the team compact while scaling up.