Hiring is one of the most important choices a company makes, but in hardtech it’s often misunderstood.

Esther Thomas and her co-founder Nain Abdi saw this up close. Before starting Colare, they worked with students and new graduates to help them improve their résumés and prepare for interviews in hardware, electronics, and automotive. What started as career coaching revealed a much bigger problem.

Software hiring normalized practical assessments years ago. Hardware teams still depend largely on résumés, interview performance, and home-built tests. Esther kept running into the same question: how can you spot hardtech engineering talent in a way that shows what they can actually do on the job?

Instead, Colare brings role-relevant work into the process earlier. A hiring team can bring an existing technical test or start with the role it needs to fill. Colare turns that material into an assessment built around the decisions that matter on the job.

With support from Robin Capital, Esther and Nain are now building a company that lets engineers show their skills in real-world situations and helps employers find the people who can really do the job. In this story, we’ll look at what she’s building, why it matters, and how Colare is changing hiring for the next generation of engineers.  

About Colare

Colare, meaning “to filter” in Latin, is an end-to-end hiring platform built for hardtech teams across industries such as automotive, aerospace, energy, and defense. Companies upload a job description; Colare maps the role to hands-on assessments across CAD, PCB design, thermal analysis, FEA, GNC, and systems problem-solving, run in the tools engineers actually use. The platform evaluates both process and output against rubrics written by senior engineers who have shipped hardware, then stack-ranks candidates and returns a detailed debrief, alongside scheduling and industry-specific hiring workflows. With stack-ranked scoring, built-in scheduling, and industry-specific workflows, Colare helps growing teams and enterprise leaders hire faster, more confidently, and with measurable improvements in the quality of their hires.

Where Colare began

The idea for Colare came from the mechanics of helping people get hired. “My first business with my co-founder, Nain, within the university was helping students and new grads optimize their resumes, prepare for interviews to get jobs in industries like hardware, electronics, and automotive,” she says.

This experience taught them how hiring really worked and how little it was connected to a candidate’s real abilities.

Esther’s cofounder Nain also saw this on the employer's side. During his time as an electrical engineer at an F100 automotive company, his manager admitted he had stopped trusting résumés because candidates who looked strong on paper kept falling apart in technical interviews. His fix was an arbitrary rule: only hire third-year students and above.

The problem was the hiring process itself. “It was only much later in the interview phase that companies even had a testing phase or had an engineer on board.”

This was very different from what they saw in other fields. Software hiring already used practical, skills-based tests, and companies evaluated candidates earlier and more directly. Whereas in hardtech, hiring still focused too much on appearances instead of what people could actually do.

The moment that made it unmissable came from a billion-dollar aerospace company. Its engineers had revolted against the résumé screen and started shipping laptops to candidates’ homes just to test their ECAD skills.

This insight became the starting point for Colare.

“There was a huge opportunity here to give more engineers the chance to actually show their skills than just make a beautiful résumé.”

Why hiring is different for hardtech

Ask Esther what most people misunderstand about hiring for hardtech, and her answer gets to the heart of Colare’s thesis. “Most people misunderstand that hardtech hiring isn’t primarily about checking if someone is ‘smart’ or has the right pedigree, it’s about whether they have engineering judgment under real constraints.”

That difference is important. In hardtech, she says, “the work lives in ambiguity: messy data, coupled systems, manufacturing reality, changing requirements.” The real challenge isn’t just knowing the right answer in theory. It’s about whether someone can think clearly when there isn’t a clear answer at all. 

Many of the systems hardware engineers deal with are physical in nature, and often mission-critical, whether it’s a rocket launch or developing new technology to produce chemicals. “The painful part is that the cost of being wrong shows up late,” she says, “so traditional proxies like résumés and conversational interviews can feel reassuring while still missing the thing that actually predicts performance: how someone makes tradeoffs and comes to decisions when there isn’t a clean answer.”

By the time companies have worked out who is a good fit, they have often lost time, money, and momentum. Résumés, polished stories, and interviews can help, but they often miss what truly matters.

That is the gap Colare is designed to address. Instead of asking candidates to talk about past work, the company runs realistic simulations that mirror the decisions they will face in the role. From there, it captures structured signals around how they reason, prioritize, and respond to constraints.

A company starts with the role it needs to fill. Colare maps that role to an assessment drawn from relevant disciplines, including CAD, PCB design, thermal analysis, finite-element analysis, and systems problem-solving. The platform evaluates both the process and final output against structured rubrics informed by senior engineers, then gives the hiring team a detailed debrief and a consistent basis for comparing candidates.

This difference is important. Colare moves role-relevant evidence earlier in the process, and hiring teams still make the final decision.

“The goal isn’t to replace human judgment; it’s to finally give teams a truthful view of it before they place a high-stakes bet.”

Why now?

 Esther is clear that Colare is not only solving an old problem, but also arriving at a moment when that problem is becoming much more urgent. “The market has just completely shifted,” she says.

“Hard tech companies from robotics to automotive to manufacturing are scaling faster than ever, and it’s become easier for new talent to enter these spaces than it was before,” she explains.

This growth creates pressure on talent. “With so much of a bigger need and investment in these spaces, the demand for labor to power it has only increased.”

AI is squeezing from the other side. “Résumés can be inflated, interview answers can be assisted, and polished profiles tell you less and less about how someone will actually perform,” she says. “Hiring demand is rising while confidence in traditional screening is falling. That gap is exactly where we sit.”

She is also careful to place AI within that broader story, rather than treating it as something detached from physical industry. “Even when thinking about AI, that needs to be supported by physical infrastructure as well.”

This is where Colare stands out. The company isn’t just fixing a hiring problem; it’s taking on a bigger workforce challenge in some of the fastest-changing industries. As engineering jobs become more specialized and important, companies need better ways to find the right people for the future.

“With the development of technology, it’s now possible for us to simulate these real engineering environments and capture meaningful performance data to get a great signal on who is the best engineer fit for your team.”

For Esther, better hiring isn’t just an administrative fix. It’s a key part of a company’s foundation.

“How can we help propel companies to have the infrastructure in place to power their technological progress?”

Building from the work outwards

Early conversations with hiring teams changed how Esther and Nain approached the product. Rather than beginning with a universal theory of assessment, they studied the workarounds companies had already created.

“One of our favorite cases was an employer who set up a camera and components on their table and instructed the candidate to guide them on which ones to select,” she remembers.

The camera setup was crude, but it revealed what the employer wanted to see: a candidate making technical choices. Examples like this pushed Colare toward discipline-specific assessments and away from a generic test.

“We got some real insights and used these to inform our product, and who needed it the most. Now, our approach is much more iterative: determine our hypothesis and goals, test them quickly, and iterate,” she says.

Esther and Nain also pressure-tested the problem through their university’s Cornerstone program. “We ended up winning it, I think largely because we found so many facts across an audit, we were talking to Ford and Toyota and all the way into manufacturing, and they all had terrible processes in place.”

“I think this, paired with the conviction that there was nothing else we wanted to do except work with each other and build a company, meant that it was time. It was time to get started.”

The problem that Colare is solving

At its core, Colare replaces weak signals with better evidence.

“Our competition is every engineer having to spend six hours with one candidate to ask them to explain Ohm’s Law,” Esther says. An ocean of generic AI assessment software is on the market, but a model trained to vet customer service reps and programmers will never tell you who makes a good GNC engineer.

Hardware has no answer key. A structural bracket, a power board, a propulsion feed system, a control loop: each has thousands of valid designs and thousands of subtly fatal ones, and the difference lives in tradeoffs, mass against stiffness, thermal margin against packaging, manufacturability against performance.

“Evaluating a space engineer means evaluating judgment about physical reality,” she says. “A GNC problem is nothing like a DFM problem, which is nothing like an RF layout. We’re always asking ourselves, how can we allow more engineers to show their skills, and how do we give businesses a better chance to get a signal?”

There’s a reason Esther keeps talking about ‘signal.’ Hiring is really about finding clear signals in a noisy environment. Résumés are just one imperfect signal, and interviews add a bit more.

But if assessments aren’t consistent or tied to real work, companies spend a lot without getting much clarity. She is aware that “overall, this is just a huge time and money sink for companies that aren’t even deriving the best results.”

In practice, there are concrete examples. At a two-person chemical manufacturing startup, a chemical engineering PhD and a business lead needed to hire its founding electrical engineer, but nobody in-house could evaluate one.

Colare became their entire engineering-hiring capability. At a subsidiary of a publicly listed manufacturer, a candidate who had impressed in every conversation was about to meet the CEO. He failed a Colare assessment built on real engineering problems, and the HR team filtered him out before he cost anyone another hour.

Elsewhere, a major manufacturer is now redesigning its engineering hiring around Colare, replacing multi-hour onsite presentations with simulations, and one company even doubled its candidate throughput in its first week on the platform.

“For Deep Tech employers, this could lead to faster decisions, more confidence in hiring, and less wasted time. For candidates, it creates another opportunity to demonstrate ability beyond credentials and interview polish.”

Hiring while building a hiring company

There’s an interesting twist in Colare’s story: the founders aren’t just solving hiring problems for others; they’re experiencing them firsthand.

Colare is now a team of six, and every one of those hires went through the same scrutiny the platform applies to candidates. Esther is deliberate about what each person needs to bring.

 “Despite being a software platform, we’re looking for a hardware-heavy team.” Experts in ME, EE, and AI talent are joining to help develop expert question sets and improve their models and evaluation algorithms.

What stands out is the type of person she is looking for. Not just technically capable, but with unusually high agency. People who can thrive in ambiguity, learn quickly, and shape the company rather than simply slot into it. “I have a view of each person at a startup as a vector. I think we’re looking for sharp and spiky people.”

It’s a striking and honest way of putting it. Early-stage startups like Colare are rarely set up by generalists. They need people with edge, curiosity, and the ability to act before everything is fully defined.

“Running a startup obviously is not easy, but it’s extremely rewarding,” she says. “When it comes to finding people that are similarly aligned, I’m a strong believer that you can figure out most things at the beginning of a company.”

 That belief also shapes Esther's view of expertise. In some roles, especially those connected to making the product industry-grade, domain depth matters enormously. In others, what matters more is whether someone can take new information, reason through it intelligently, and apply it well.

At this stage, every hire is more than just extra help. Each one shapes the company's future.

“Every single hire has the potential to completely accelerate our company.”

Getting through the hard days

Despite all the product thinking and market insight behind Colare, Esther’s motivation is deeply human.

“Colare first started because Nain and I witnessed ourselves as students and new grads who, despite being brilliant engineers, maybe lacked the right keywords on their résumé and got filtered out before they had any opportunity to show their skills during the interview process.”

This experience continues to guide her. Even though Colare is a B2B company, Esther sees its core mission as supporting candidates. It’s been built to help employers hire better and to help talented people be seen for who they really are.

The most rewarding moments, she says, are hearing about people who might otherwise have been overlooked.

Another big source of energy for Esther is the person building Colare with her. She speaks warmly about her co-founder, Nain, who is also her close friend. “I’m lucky to be working with my brilliant best friend of 8 years, Nain, so our office is always filled with lots of laughs that make everything worth it,” she shares.

That might be the clearest sign of Colare’s purpose. Behind all the talk of signal, systems, and infrastructure is a much simpler idea: good people deserve a better chance.

“There is nothing better than hearing some of the stories of companies that found their diamonds in the rough through our simulations.”

Quick-fire round

A tool you can’t live without?

“In the most basic sense - a notebook and pen. I fear most of it is illegible to someone else, but most of my base notes, thoughts, and plans first start there.”

How do you recharge?

“A 20-minute call with my mom usually sets me straight.”

Advice that stuck:

“You never know how much time you actually have in the day. I heard that line when I was near the end of high school, and ever since it has made me think about the intentionality of my time and what was possible if I really dedicated my time to things that I loved and cared about.”

What’s next?

Ask Esther what success looks like for Colare beyond revenue or growth, and her answer goes straight to the company’s larger ambition: “We want to increase the velocity of building in the physical world.”

It’s a powerful way to put it because it shows that Colare isn’t just about hiring efficiency. It’s about what better hiring makes possible.

In Esther’s vision, “five to ten years from now, success means that Colare becomes the default standard for high-stakes technical hiring: proof over pedigree, validated like a design.”

In that future, the best engineers spend less time proving themselves and more time building. Teams get up to speed faster because they know not just who someone is on paper, but where they will shine, where they’ll need support, and how to help them succeed.

As Deep Tech becomes increasingly automated and AI-forward, Esther sees Colare as even more foundational: a predictive layer that helps companies keep pace with evolving roles and skill requirements.

It’s an ambitious goal, but it aligns with how Esther has talked about the problem from the start: not just a workflow issue, but something that limits what great teams can actually build 

Get to know the company here and watch this space.