This episode looks at SmoothHiring, the Worthington, Ohio company behind an AI hiring platform built to predict which candidates will succeed and stay, rather than simply processing applications faster. Markus explores how patented behavioural science sits alongside applicant tracking, automated job distribution across 200+ boards, skills assessments and one way video interviews, and why carrying the platform past the offer letter into onboarding and performance closes a loop the industry has left open for decades. A thoughtful listen for anyone who has ever hired on instinct and hoped for the best.
Here is a number that should bother every business owner listening right now. Most hiring decisions are made on the strength of a document the candidate wrote about themselves, and a conversation that lasts under an hour. We would never buy a building that way. We would never sign a supplier contract that way. And yet we bring people into our companies, people who will shape the culture and the output and the mood of the place for years, on the basis of a resume and a gut feeling.
Welcome back to The Next Biz Thing. I am Markus J. Diplama, and this is the show where I go looking for the companies quietly solving problems that everybody else has simply learned to live with. Some of the businesses I cover are tiny. Some are already at scale. What they have in common is that somebody looked at a broken process, decided it did not have to stay broken, and built something better. Today's company is very much in that second camp, and the process it is fixing is one that touches absolutely every organisation on earth.
The company is SmoothHiring, and they are based in Worthington, Ohio, just north of Columbus. What they have built is an AI hiring platform, and their promise is unusually specific. They do not claim to help you find more candidates. They claim to help you find the ones who will actually succeed. That distinction matters more than it sounds, and I want to spend some time on it, because it goes to the heart of why hiring feels so unreliable for so many people.
Think about what a traditional applicant tracking system does. It collects applications. It sorts them. It lets you move people through stages, schedule interviews, send rejections. It is, essentially, a filing cabinet with a workflow attached. Useful, certainly. But notice what it does not do. It does not tell you anything about whether the person you are about to hire will thrive in your particular role, in your particular team, in your particular company. That judgement is still left entirely to a human being, working from a resume that was written to impress and an interview where everybody was on their best behaviour.
SmoothHiring's answer to that is predictive hiring, built on patented technology that draws on behavioural science rather than on document parsing. The platform is designed to identify the candidates most likely to succeed and, crucially, most likely to stay. Retention is the part people forget. A hire who leaves in four months is not a neutral outcome. It is the recruiting cost, the onboarding time, the ramp-up period, the disruption to the team, and then the whole cycle beginning again. Getting the prediction right the first time is worth an enormous amount, and it is worth it quietly, in ways that never show up as a line item.
Now, the platform itself is genuinely broad, and I think that breadth is part of the story. There is the applicant tracking system at the core. There is automated job distribution, which pushes a posting out to more than two hundred job boards without anybody having to copy and paste a description two hundred times. There is AI candidate screening and ranking, which does the first pass through a pile of applications. There are behavioural and skills assessments. There are one way video interviews, so a candidate can record their answers on their own schedule and a hiring manager can review five of them in the time it would have taken to sit through one live call. There is interview scheduling. And then, once somebody is hired, it keeps going: employee onboarding, time and attendance tracking, performance management, engagement tools.
That last part is what caught my attention. Most hiring software stops at the offer letter. It treats the job as done the moment the contract is signed, which is a strange place to stop, because the moment the contract is signed is when the actual question begins. Did this work? Did we get it right? SmoothHiring carries on past that line, and in doing so it closes a loop that the industry has left open for decades. If the same platform that predicted a candidate's success is also the platform tracking their performance six months later, then the prediction has something to be measured against. That is how a system gets better rather than just getting bigger.
More than eight thousand companies are using it, which tells you this is not a concept looking for a market. It is a product that a lot of people have already decided is worth paying for. And the testimonials on the site are refreshingly unglamorous. One customer talks about the accuracy and the ease of use, which are the two things that actually matter and almost never come together. Another mentions hiring ten employees at a fraction of what traditional recruiters would have charged. That is the kind of feedback that tells you the tool is being used by real people with real budgets, not just admired from a distance.
Let me put this in some context, because I think the hiring technology space is one of the more interesting places to be watching right now. For about twenty years, the dominant idea in recruitment software was efficiency. Handle more applications. Handle them faster. Reduce the cost per hire. All of that made sense, and all of it delivered real gains. But it also produced a subtle problem, which is that a system optimised for throughput will happily process the wrong candidate very efficiently. Speed is only a virtue if you are moving in the right direction.
What is happening now is a shift from efficiency toward accuracy. The question has changed from how many applications can we handle to which of these people should we actually hire. That is a much harder question, and it requires a different kind of technology. Parsing a resume is a text problem. Predicting whether somebody will succeed in a role is a behavioural problem, and behavioural problems need behavioural science underneath them. This is exactly where SmoothHiring has planted itself, and it is why the patented element of what they do is worth taking seriously rather than treating as marketing garnish.
There is also something worth saying about fairness here, because it is a real consequence of this approach rather than a nice side effect. When hiring decisions rest on resumes, they inherit everything a resume carries with it. Where you went to school. Which companies happened to give you your first break. How confident you were feeling on the day you wrote it. How good you are at the specific and quite unusual skill of writing about yourself. None of those things are the same as being good at the job. A system that assesses behaviour and skills directly is looking at something closer to the thing that actually matters, and that tends to open doors for capable people whose paperwork never quite told their story.
I also like that this is coming out of Worthington, Ohio, rather than one of the coastal technology hubs. There is a version of the software industry that only ever gets written about from two or three zip codes, and it leaves out an enormous amount of what is actually being built. A company solving a universal business problem from central Ohio, serving eight thousand companies, is a reminder that good products come from wherever somebody understands the problem well enough. Being close to a wide range of ordinary businesses, rather than to venture capital, is arguably an advantage when the thing you are building has to work for a manufacturer and a clinic and a retailer and a professional services firm alike.
So why should you care about any of this if you are not currently hiring? Because the underlying idea travels a long way beyond recruitment. What SmoothHiring is really arguing is that a decision most people make on instinct can be made on evidence instead, and that the evidence was always available, we just were not collecting it or using it well. That argument applies to a great many things in business. We have all watched an important call get made because somebody in the room felt strongly about it. Sometimes that works. But it does not scale, it cannot be examined, and when it goes wrong nobody can say why.
Hiring is a particularly good place to start replacing instinct with evidence, because the stakes are so high and the feedback loop is so long. You find out whether a hire was right months after you made the call, by which point the reasoning has faded and nobody is going back to check. Tools that close that gap do something more valuable than saving time. They make it possible to learn.
If you are running a company, or leading a team, or sitting in a hiring process right now wondering how on earth you are supposed to choose between twelve people who all interview well, go and look at what SmoothHiring is doing. Look at how the assessments work. Look at how the prediction piece fits alongside the ordinary tracking and scheduling. Even if you never buy it, the way they have framed the problem will change how you think about the next hire you make.
That is where I will leave it for today. My thanks to the team at SmoothHiring for building something that takes the hardest part of running a business seriously. If this episode gave you something to think about, share it with someone who is hiring at the moment. They will thank you.
I am Markus J. Diplama, this has been The Next Biz Thing, and I will see you next time.
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