Hiring decisions, backed by hard proof.

By the mid-2020s Gatik had moved well beyond pilots. The company was operating fully driverless box trucks on commercial routes for major retailers, completing tens of thousands of orders with high on-time performance and securing hundreds of millions in contracted revenue. Scaling the fleet and the underlying autonomy stack required rapidly expanding a specialized robotics engineering team — engineers capable of writing and maintaining low-level C++ for safety-critical systems that had to perform reliably on public roads.

Traditional hiring processes could not keep up. Resume screens, phone interviews, multiple technical rounds, and whiteboard sessions consistently failed to reveal whether candidates could actually produce production-quality, safety-conscious C++ for real-time, resource-constrained, fail-safe robotics systems. Strong interview performers frequently struggled when faced with the real work. The result was predictable and costly: engineering panels spent hundreds of collective hours interviewing candidates who ultimately could not do the job, and the full robotics engineering hiring loop stretched to roughly six weeks, slowing Gatik’s ability to staff up as commercial demand accelerated.

Gatik needed a way to access proven talent without waiting for lengthy screening and assessment cycles. We turned to EvexAI. EvexAI had already completed the intensive early-stage work: performance-based work trials and rigorous technical assessments conducted inside real-world systems simulation environments that closely mirror the conditions Gatik’s autonomy stack operates under. Candidates who demonstrated the required low-level C++ skills and safety-critical engineering judgment were fully vetted in advance.

When Gatik described the exact type of robotics engineering talent they needed, including the specific technical requirements, experience level, and performance expectations, they immediately received a shortlist of already-vetted candidates, each backed by clear performance proof from those completed trials. No additional waiting for screening or skill validation was required. The engineering team could move directly into focused panel interviews and final decision-making.

I’m Jose Murillo, founder of Primero. We build real AI transformation projects for enterprises across Latin America — custom LLM tuning, messy enterprise integrations, the kind of work that has to work in the real conditions of different markets, different data realities, different languages, different infrastructure. Delivery timelines are tight. Clients don’t care how hard the talent market is. They care that the team we put in front of them can actually execute.

For a long time the biggest bottleneck wasn’t the work itself. It was finding people who could actually do it. We would get candidates who looked strong on paper and sounded sharp in interviews. Then, once they were on a real project, the gaps showed up. Custom model tuning that fell apart under production constraints. Integration work that looked clean in a slide deck but broke when it hit the actual systems. Every time it happened we lost days, sometimes weeks, and it put pressure on the teams already carrying the load.

We tried the usual things. Longer technical interviews. Take-home challenges. Multiple rounds. It just slowed everything down and still didn’t give us a clear signal. The process was burning our senior people and still leaving us uncertain about who we were putting on client work. When we found out about EvexAI, we started using it.

What changed is simple: by the time we talk to someone, the hard part is already done. EvexAI has already put candidates through secure, localized benchmark challenges designed specifically for the level of AI work we do. When we need people, we describe exactly what we need — the technical depth, the type of enterprise integration experience, the ability to operate across different LATAM environments — and we get a shortlist of people who have already been measured on the real skills. Not interview performance. Actual capability.

No waiting for a new screening process to start. No more hoping the next interview will finally reveal the truth. We just get the list, with the proof attached, and we can move. The difference showed up fast. We stopped wasting senior engineer time on people who weren’t going to make it. We could staff projects with more confidence. And because we could consistently put stronger teams in front of clients, we started winning more of the enterprise deals that used to feel out of reach.

For a long time we kept losing people late. We would invest weeks in someone. They would pass the early screens. They would look strong in conversation. Then in the final rounds, when we put them in front of a real product scenario or a mock client briefing, the cracks would show. Either the technical floor wasn’t high enough, or they couldn’t explain the value without sliding into feature dumping. Every time it happened we lost another senior person’s time, another week of pipeline, and a little more confidence in our own process.

The drop-off rate in those final rounds was killing us. Offer acceptance was inconsistent because candidates could feel the uncertainty on our side too. We started using EvexAI.

What I like is that the hard evaluation is already finished before we ever see a name. EvexAI runs custom performance trials that combine secure coding exercises with mock client product briefings. By the time a candidate reaches us, they have already been measured on both the technical threshold and the consultative communication skills the role actually requires.

When we need people — sales engineers, product marketers, whoever has to sit between the product and the customer — we just describe exactly what we need. We get a shortlist of people who have already proven they can do both sides of the work. No more hoping the next final-round interview will finally give us a clear signal. The signal is already there.

The change was immediate. Almost every person who reaches the final stage now is already pre-qualified on the things that used to eliminate them. Executive time stopped getting wasted. Candidates feel the alignment earlier, which is a big reason our offer acceptance rate moved to 90%. And the people we bring on actually match the work from day one.

I got tired of hiring people who looked perfect and then disappeared after three months. I’m Daksh Gupta, CEO of Greptile. We build AI tools that help developers search and understand massive codebases. Our buyers are sophisticated engineering leaders. That means the people on our side, especially in sales and the executive roles that sit close to the product, can’t just be good talkers. They have to actually understand how complex software gets built and sold.

For a long time our hiring process kept failing us in the same way. We would run the usual interviews. Smart people. Strong résumés. Good energy. Then they would join and the reality would hit. They couldn’t navigate the actual product conversations with technical buyers. They needed too much hand-holding. Or they simply didn’t have the high-agency drive to push real work forward without constant direction. We ended up with false-positive hires — people who passed every interview signal and still didn’t perform once they were inside the company. Retention suffered. Momentum suffered.

Leetcode-style questions and polished interview loops were not telling us who could actually operate in our environment. We switched to EvexAI.

What matters to me is that the real evaluation is already finished before a candidate ever reaches us. EvexAI runs work trials that feel like the actual job — realistic scenarios that test how someone navigates complexity, communicates with technical stakeholders, and drives outcomes without being told what to do every step.

When we need sales people or executive-level hires, we just describe exactly what we’re looking for. We get a shortlist of people who have already been measured on the things that used to fool us. No more waiting for a new process to start. The proof is already attached. Since we made the change we have had zero false-positive hires in those roles. The people who join perform. They stay. They push real work from the beginning. That clean record is not an accident. It comes from finally testing for the actual job instead of testing for interview performance.

I don’t gamble with security hires. I’m Alex Grinman, co-founder and CTO of Footprint. We build security and compliance infrastructure. When we bring someone into a senior infrastructure role, they’re going to touch systems where a single bad habit can create real exposure. Cryptographic choices, secure protocol implementation, API design under real constraints — these aren’t things you can fully evaluate in a conversation or a take-home that never gets pressure-tested.

For a long time the screening process left me exposed. We could ask the right questions. We could talk through threat models. Candidates would say all the right things about secure development practices and compliance. Then we’d get into the actual work and discover gaps — shortcuts under time pressure, incomplete understanding of cryptographic trade-offs, design decisions that looked clean until you examined them closely. By then we had already invested time, extended an offer, and brought someone into an environment where mistakes are expensive.

Traditional interviews were not giving me auditable proof. They were giving me confidence theater. We started using EvexAI.

What changed is that the evaluation is already finished before a candidate reaches us. EvexAI runs candidates through a sandboxed environment where they have to actually implement secure protocols and API designs under realistic conditions. By the time we look at someone, we already have concrete evidence of how they write security-critical code, not how they talk about it.

When we need senior infrastructure people, we describe exactly what the role requires. We get a shortlist of candidates who have already been measured on the things that used to create risk for us. No waiting for a new assessment cycle to begin. The proof is already there.

Since we made the switch we have had 100% secure-coding compliance on the people we’ve hired into these roles. We completely mitigated the screening risk that used to keep me up at night. Every formal offer now goes out with clear, auditable evidence that the person already demonstrates security-first habits under pressure.