Experts Without the LinkedIn Noise

01 /The Concept

The expert marketplace is a category defined by broken trust. Most platforms are flooded with self-declared consultants whose credentials amount to a polished LinkedIn headline and confident pricing. Ethos was built around a different premise: that genuine expertise leaves a verifiable digital trail, and finding it shouldn't depend on who's loudest.

The use cases range from market or technology consultations to investment and governance advice, expert surveys, conference speakers, fractional executives, board members, and even full-time specialists.

The process is simple: a client describes in plain language who they're looking for and on what topic, and the platform returns a short list of the most relevant candidates within minutes. The client reviews profiles, selects the experts they'd like to hear from, and sends requests for online calls – which experts can accept or decline based on their availability.

Expert profiles remain anonymous. They contain only information that confirms expertise without identifying the individual. Profiles are auto-generated by the platform, but experts can request corrections.

Clients pay per call, and the platform takes a commission. For an additional $249 per month, clients get access to a library of call transcripts, a company database, and integrations with their own systems.

Experts set their own rates and can adjust them at any time based on demand – which naturally rises with more calls on the platform.

Ethos currently counts 25 global investment and consulting firms among its primary clients, though the startup plans to expand its coverage of industries and use cases soon. It has raised $3.25 million in its first funding round.

02 /Why It Matters

At first glance, another expert marketplace sounds like a non-starter. Self-declared experts are everywhere, and the loudest voices and shiniest résumés often have the least correlation with actual knowledge.

That's precisely the problem Ethos is trying to solve. As the startup puts it in its mission statement: "expertise cannot be assessed by a résumé or a follower count alone."

So the Ethos AI engine crawls and analyzes a much broader set of signals – academic publications, GitHub repositories, portfolios, blogs – and builds something like an industry influence graph that reflects each person's real track record and standing within a field.

From millions of nominally qualified candidates, the platform can surface the ten who actually know what they're talking about.

A related approach is used by Beatrust ([related review](/review/kak-najti-togo-kto-nuzhen)), which raised $9.1 million for a similar problem on a different market. Beatrust's platform helps large enterprises find internal experts – employees with deep knowledge of a specific topic – for consultations or project teams. Its AI engine digs through internal document repositories, presentations, and reports to map expertise across the organization.

The problem Beatrust addresses is real: in large companies, employees often don't know their colleagues well enough to find the right internal expert, so they turn to expensive outside consultants who don't understand the company's context. Internal discovery solves both issues at once.

03 /Opportunities

The broader challenge is finding the right people without relying on self-promotion. The rise of personal branding on social media has created an attention economy where visibility frequently outpaces actual ability. As the saying goes, not all that glitters is gold.

But expertise does leave a digital trail – it's just less visible than a viral post. And that's exactly where AI can help: synthesizing and cross-referencing a large volume of weak signals to surface strong conclusions.

The direction worth pursuing: platforms that use AI to detect and analyze digital evidence of real-world expertise, across different verticals.

One compelling example is Y Combinator graduate Verata ([covered previously](/review/chtoby-pobedit-konkurentov-nuzhno-znat-chto-u-nih-proishodit)), which built a tool for private equity funds to identify top executives for portfolio companies. Its AI estimates company revenue trajectories from indirect signals and cross-references them against executives' tenures – surfacing only those leaders who actually grew revenue in the relevant sectors.

Where else does the "find real experts" problem exist? What digital traces do experts leave in those fields? How can those traces be found, analyzed, and benchmarked?

One example: a platform for evaluating sales consultants – pulling company names and engagement periods from their résumés, then cross-referencing with estimated revenue changes during those periods. No verifiable track record, no listing. A similar approach could theoretically work for executive coaches: analyze how their clients' careers progressed afterward.

Of course, transparent platforms like that might shrink certain consulting markets considerably. Better to target areas where genuine experts actually exist – and where companies are willing to pay serious money to find them. What are those areas?