Why I built Vetano: the bias hiring tools won't fix

In 2023, I got caught in a big tech layoff after 20 years in the industry. For months I interviewed and nothing worked. Phone screens that went well stopped converting. Final rounds went cold. I started to recognize a pattern I had been recognizing for most of my career, and I started thinking about whether there was a better way for hiring to evaluate people in the first place.

This essay is the honest version of why Vetano exists, what it does about bias in hiring, and what it does not pretend to solve. If you care about responsible hiring, I want you to read it as a peer, not as a prospect.

The conference room

One story stays with me.

A Fortune 100 company reached out after seeing my resume. They wanted help fixing their security issues. The phone conversation went well enough that they asked if I could come to NYC for an immediate interview. I took the train in that day.

When I got there, someone walked me into a conference room and left me alone. I waited about twenty minutes while various people walked past the door. Then someone came in and told me the team had reviewed my resume and decided I did not have enough experience after all. Not a good fit. They thanked me for my time.

I thanked them, left the building, and got back on the train.

I knew what had happened. They had not reviewed my resume in those twenty minutes. They had reviewed me. The resume had been fine on the phone. Something else changed when I walked through the door.

I had been preparing for moments like that for most of my career. It was not the first time. It would not be the last.

The thought that came to me on the train home was not anger. It was efficiency. If this was going to happen anyway, I wanted it to happen before I got on the train. I wanted the version of bias that wasted less of my life. And I wanted, if I was going to be evaluated, to be evaluated on more than a piece of paper that the wrong reader could discard for the wrong reason.

That is what Vetano tries to do.

Resumes are not bias-neutral

The standard objection to a video-first hiring platform is that video introduces visible characteristics that resumes do not show until later in the process. Race, age, gender, appearance, accent, body language. The concern is real and worth taking seriously.

The honest framing is that resumes aren’t bias-neutral either. They are a different kind of biased.

Bertrand and Mullainathan’s field study, "Are Emily and Greg More Employable than Lakisha and Jamal?", showed that identical resumes with white-sounding names received roughly 50% more callbacks than those with Black-sounding names. Decades of follow-up research have shown resumes get filtered on names, schools, employment gaps, ZIP codes, and dozens of signals that have nothing to do with capability. Both human and algorithmic screeners do this.

So the choice is not "biased video" versus "unbiased resume." The choice is between two flawed systems. Resume screening hides bias behind a veneer of objectivity, happens with less data, and happens with no chance for the candidate to present themselves as a whole person. Video screening surfaces visible signals earlier, with more data, and lets the candidate at least be present in their own evaluation.

I would rather be filtered out for who I am while I have a chance to speak than filtered out for a name on a piece of paper while I never get the call.

The cost of AI screening on resumes

In May 2026, Stanford HAI published the first large-scale empirical study of AI hiring tools in active use. The researchers followed 3.4 million applicants submitting 4 million applications across 1,700 job postings, 150 employers, and 11 industries, all screened by a single third-party AI vendor.

The findings are hard to look away from. 26 percent of Black applicants and 15 percent of Asian applicants applied to positions where the AI screener discriminated against their racial group, measured against the EEOC's four-fifths rule, the legal standard for adverse impact under Title VII. If the AI had recommended these candidates at the same rate as the most-favored group, roughly 40,000 more applications would have advanced.

The researchers also documented what they call "algorithmic monoculture." When many employers depend on the same AI vendor, candidates get systematically rejected from every job they apply to in ways that do not happen in non-AI hiring. 10 percent of applicants who submitted four or more applications were rejected from all of them.

There is a methodological point in this work that matters. When bias is measured by pooling all positions together, the way vendors typically report it, it appears to disappear. When measured job-by-job, the discrimination is clear. The aggregate metrics in compliance reports have been hiding the actual harm.

The tools that have been claiming to reduce bias have been making the bias worse, on a different layer of the funnel and with less accountability than the human screeners they replaced.

Vetano is structured differently. Not because we claim to have solved bias. That claim is exactly the kind of overclaim the field has been making for decades. The inputs to evaluation are different. Verified identity instead of names on a page. Demonstrated skill instead of credentials parsed by an algorithm. Candidate-controlled self-presentation instead of a filtered document. The failure modes the Stanford study documents operate on the layer Vetano replaces.

The same scrutiny should apply to Vetano as to any AI vendor in the space. Hiring tools that claim to reduce bias should be willing to be studied. Their methodology should be transparent. Their outcomes should be measurable against legal standards like the four-fifths rule. That is the path forward.

Sources: Stanford HAI, AI Hiring Tools Can Yield Racial Bias and Systemic Rejection and Fortune coverage.

What Vetano actually does about bias

There are three concrete things Vetano does that move the bias conversation forward, and I want to be specific about each.

1. Identity is verified. Every candidate goes through Persona, the same identity verification provider used by Coinbase, Square, and Robinhood. The candidate uploads a government-issued ID, submits a selfie, and Persona’s biometric matching confirms the person is real. Verification data is used only for verification. It is not sold, not repurposed, not used for ad targeting. For employers, this removes a class of identity fraud that resumes do nothing about.

2. Skill is demonstrated, not just claimed. Candidates record short videos that show how they think, how they communicate, and where appropriate, how they work. That demonstration is the most legitimate criterion any hiring system can use, and it does not require a credential to access it. A candidate without a fancy degree can compete on the same footing as a candidate with credentials. That helps people from non-traditional backgrounds, which is the population DEI work is supposed to be helping.

3. Review is structured. Employers see profiles built around the same components: an intro video, skill or scenario videos, verified work history, and references. The structure encourages comparison on capability, not on resume gloss. It does not eliminate human bias, but it reduces the role of pure subjective impression that unstructured review invites.

These are not claims that Vetano "solves" bias. Nothing solves bias. They are the specific mechanisms by which the product tries to do better than the system it replaces.

What about roles where skill is harder to show on video?

This is the most legitimate product question I get, and the honest answer is that video works best where skill is most directly demonstrable. A barber’s fade, a bartender’s pour, a line cook’s knife work, a welder’s bead, a stylist’s cut. These are unmistakable on video, and resumes cannot show them.

But the platform also improves the hiring signal for roles where skill is more cognitive than physical. An analyst can walk through their thinking on a market problem. A lawyer can explain a complex case. An engineer can work through a system design out loud. A salesperson can deliver a real pitch. A designer can show their work and talk through the decisions behind it. These videos give employers a window into how someone thinks and communicates, which is what they were trying to evaluate in the interview anyway, just on a more accurate signal than a resume can provide.

On location. Most candidates record wherever makes sense for showing the skill. Bartenders record cocktail technique in their own kitchens. Cooks film knife work at home. Makeup artists work on themselves or volunteer models. Designers walk through their portfolios on screen recordings. Barbers can show technique on a mannequin head, on a friend, or in their own chair at home. The point is to demonstrate the capability, not to recreate the workplace.

For service roles where the work is interpersonal, candidates use intro videos to show presence and communication, scenario responses to demonstrate how they handle real situations, and verified work history with recommendations from previous managers. Not equally effective for every role, but the alternative is not "perfect evaluation for some roles" versus "imperfect evaluation for others." The alternative is "imperfect evaluation through video" versus "biased and incomplete evaluation through resume."

For nearly every role, video plus verification is a better starting point than a piece of paper.

What Vetano does not solve

I want to be clear about the limits.

Vetano does not eliminate bias. A hiring manager who is going to discriminate is still going to discriminate. What Vetano changes is when the discrimination happens, how much data the candidate has been able to put in front of the decision, and how much of the candidate’s time the system wastes in the process.

Vetano does not guarantee any specific hire is fair. It changes the structure of the system, not the conscience of every person inside it.

Vetano is not the only signal an employer should use. Reference calls, structured interviews, and trial work all still matter. Video is a stronger first signal than a resume. It is not a complete picture on its own.

And Vetano is not a substitute for the harder work of building inclusive cultures. A platform can change the front door of hiring. It cannot change what happens after someone walks through it.

Why this is the project I keep working on

If you have read this far, you can tell I do not think Vetano is a finished product or a complete answer. It is a better front door than the one we have now. It is built by someone who has spent his career on the receiving end of the system it is replacing. And it is honest about what it does and what it does not.

The full founding story, including the neighbor who put $5,000 in a bank envelope and told me to stop selling shades and start the company, lives on our about page.

If you work in HR, DEI, or research on hiring bias and you want to pressure-test how Vetano handles any of this, I want to hear from you. That kind of conversation is what makes the product better.