Resumes are optimized, not honest AI makes it trivially easy to tailor a resume to any job description. What reads as a perfect fit on paper is often a perfect fabrication.
Interviews reward performance, not capability Polished candidates rehearse answers. AI-assisted candidates script them. Neither tells you if they can ship production code under pressure.
Generic tests don't match real work Standard coding tests measure whether someone can solve algorithm puzzles. They don't measure whether someone can do the actual work the role requires.
Skills fraud is the new frontier Candidates are using AI tools during evaluations to demonstrate capability they don't actually have. In our most recent engagement, 20% of candidates were flagged.
We understand the problem We work with engineering leaders hiring AI, ML, and advanced technical talent every day. We've watched resumes lose their signal. We've seen candidates pass interviews they shouldn't have passed. We've seen hiring teams add more process without getting more confidence. The problem isn't that you're not screening hard enough. It's that the signals you're screening on are no longer reliable.
How we solve it We use AI to identify the true capabilities of every candidate. Not their resume. Not their interview performance. Their actual, demonstrated ability to do the work. Every candidate completes a role-specific work sample in a controlled, proctored environment. AI evaluates their code, their reasoning, their decision-making, and how they use AI tools, in real time. Human evaluators validate the work independently alongside. The result is a candidate profile built on observed performance, not self-reported claims.
Signal You have candidates. You need proof. Role deconstruction & capability architecture AI proctoring with fraud detection Validated candidate profiles with reviewable evidence
Signal + Insight You need proof and clarity. Everything in Signal, plus: Custom-built work sample Human-in-the-loop proctoring
Signal + Insight + Strategy You need a recommendation and a plan. Everything in Signal + Insight, plus: Candidate recommendation with rationale 90-day onboarding and development plan Decision framework with contingencies Findings presentation with Q&A Talent strategy
What does Vero do? Vero validates senior AI, ML, and advanced technical talent before the offer goes out. We design role-specific work samples, run them under proctored conditions, and return structured capability markers the hiring manager can review.
How is Vero different from a coding test or a take-home challenge? Standard coding tests measure whether a candidate can solve algorithm puzzles. Take-home challenges are now solved with AI assistance roughly 70% of the time, often without disclosure. Vero builds a custom work sample for the specific role, runs it under proctored conditions where AI use is observable, and returns a reviewable artifact rather than a pass/fail score.
Does Vero place candidates? No. Vero is a skills validation offering, not a recruiting service. We evaluate the candidates a hiring leader already has. This neutrality is what makes the offer credible.
What roles does Vero evaluate? Senior AI engineers, ML engineers, data scientists, and advanced technical roles where the cost of a wrong hire runs $200,000 to $500,000 fully loaded plus six to twelve months of lost momentum.
How long does a Vero engagement take? Most engagements complete within days to weeks depending on the tier and the number of candidates. The Signal tier returns validated capability profiles fast. The Signal + Insight + Strategy tier includes a full recommendation and onboarding plan.
How does Vero handle AI use during the evaluation? AI use is tracked, not blocked. How a candidate uses AI is itself a signal worth observing. Both AI and human validators review the work independently, and disagreements are surfaced rather than averaged.